diff --git a/docs/source/en/model_doc/idefics2.md b/docs/source/en/model_doc/idefics2.md
index 5b91fcf38cd7b5..a66fa03a88fcea 100644
--- a/docs/source/en/model_doc/idefics2.md
+++ b/docs/source/en/model_doc/idefics2.md
@@ -27,13 +27,18 @@ images, or simply behave as a pure language model without visual inputs. It impr
 document understanding, OCR, or visual reasoning. Idefics2 is lightweight (8 billion parameters) and treats
 images in their native aspect ratio and resolution, which allows for varying inference efficiency.
 
-Tips:
+This model was contributed by [amyeroberts](https://huggingface.co/amyeroberts).
+The original code can be found [here](https://huggingface.co/HuggingFaceM4/idefics2).
+
+## Usage tips
+
 - Each sample can contain multiple images, and the number of images can vary between samples. The processor will pad the inputs to the maximum number of images in a batch for input to the model.
 - The processor has a `do_image_splitting` option. If `True`, each input image will be split into 4 sub-images, and concatenated with the original to form 5 images. This is useful for increasing model performance. Make sure `processor.image_processor.do_image_splitting` is set to `False` if the model was not trained with this option.
 - `text` passed to the processor should have the `<image>` tokens where the images should be inserted. And `<end_of_utterance>` at the end of each utterance if the text is a chat message.
 - The processor has its own `apply_chat_template` method to convert chat messages to text that can then be passed as `text` to the processor.
 
 Example of how to use the processor on chat messages:
+
 ```python
 import requests
 from PIL import Image
@@ -56,20 +61,30 @@ messages = [{
 }]
 
 processor = Idefics2Processor.from_pretrained("HuggingFaceM4/idefics2-8b")
-model = Idefics2ForConditionalGeneration.from_pretrained("HuggingFaceM4/idefics2-8b")
+model = Idefics2ForConditionalGeneration.from_pretrained("HuggingFaceM4/idefics2-8b", device_map="auto")
 
-text = processor.apply_chat_template(messages)
-# "User: What’s the difference between these two images?<image><image><end_of_utterance>\n"
-print(text)
+# at inference time, one needs to pass `add_generation_prompt=True` in order to make sure the model completes the prompt
+text = processor.apply_chat_template(messages, add_generation_prompt=True)
 
-inputs = processor(images=images, text=text)
+inputs = processor(images=images, text=text, return_tensors="pt").to("cuda")
 
-generated_text = model.generate(**inputs)
+generated_text = model.generate(**inputs, max_new_tokens=500)
+generated_text = processor.batch_decode(generated_text, skip_special_tokens=True)[0]
+print("Generated text:", generated_text)
 ```
 
-This model was contributed by [amyeroberts](https://huggingface.co/amyeroberts).
-The original code can be found [here](https://huggingface.co/HuggingFaceM4/idefics2).
+## Model optimizations
+
+By default, weights are loaded in float32 (32 bits per parameter). However, one can speed up the model significantly by leveraging Flash-Attention-2.
+
+
+
+## Resources
+
+A list of official Hugging Face and community (indicated by 🌎) resources to help you get started with Idefics2. If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we'll review it! The resource should ideally demonstrate something new instead of duplicating an existing resource.
 
+- A notebook on how to fine-tune Idefics2 on a custom dataset using the [Trainer](../main_classes/trainer.md) can be found [here](https://colab.research.google.com/drive/1NtcTgRbSBKN7pYD3Vdx1j9m8pt3fhFDB?usp=sharing). It supports both full fine-tuning as well as (quantized) LoRa.
+- A script regarding how to fine-tune Idefics2 using the TRL library can be found [here]().
 
 ## Idefics2Config
 
diff --git a/docs/source/en/model_doc/mistral.md b/docs/source/en/model_doc/mistral.md
index 0ab214206165f1..b2c011c19f18bb 100644
--- a/docs/source/en/model_doc/mistral.md
+++ b/docs/source/en/model_doc/mistral.md
@@ -18,7 +18,7 @@ rendered properly in your Markdown viewer.
 
 ## Overview
 
-Mistral was introduced in the [this blogpost](https://mistral.ai/news/announcing-mistral-7b/) by Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed.
+Mistral was introduced in [this blogpost](https://mistral.ai/news/announcing-mistral-7b/) by Albert Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, William El Sayed.
 
 The introduction of the blog post says:
 
@@ -51,39 +51,39 @@ The Mistral team has released 3 checkpoints:
 The base model can be used as follows:
 
 ```python
->>> from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
->>> model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", device_map="auto")
->>> tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
+model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
 
->>> prompt = "My favourite condiment is"
+prompt = "My favourite condiment is"
 
->>> model_inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
->>> model.to(device)
+model_inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
+model.to(device)
 
->>> generated_ids = model.generate(**model_inputs, max_new_tokens=100, do_sample=True)
->>> tokenizer.batch_decode(generated_ids)[0]
+generated_ids = model.generate(**model_inputs, max_new_tokens=100, do_sample=True)
+tokenizer.batch_decode(generated_ids)[0]
 "My favourite condiment is to ..."
 ```
 
 The instruction tuned model can be used as follows:
 
 ```python
->>> from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
->>> model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2", device_map="auto")
->>> tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
+model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
 
->>> messages = [
-...     {"role": "user", "content": "What is your favourite condiment?"},
-...     {"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
-...     {"role": "user", "content": "Do you have mayonnaise recipes?"}
-... ]
+messages = [
+     {"role": "user", "content": "What is your favourite condiment?"},
+     {"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
+     {"role": "user", "content": "Do you have mayonnaise recipes?"}
+]
 
->>> model_inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
+model_inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
 
->>> generated_ids = model.generate(model_inputs, max_new_tokens=100, do_sample=True)
->>> tokenizer.batch_decode(generated_ids)[0]
+generated_ids = model.generate(model_inputs, max_new_tokens=100, do_sample=True)
+tokenizer.batch_decode(generated_ids)[0]
 "Mayonnaise can be made as follows: (...)"
 ```
 
@@ -104,19 +104,19 @@ Make also sure that you have a hardware that is compatible with Flash-Attention
 To load and run a model using Flash Attention-2, refer to the snippet below:
 
 ```python
->>> import torch
->>> from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
->>> model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", torch_dtype=torch.float16, attn_implementation="flash_attention_2", device_map="auto")
->>> tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
+model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-v0.1", torch_dtype=torch.float16, attn_implementation="flash_attention_2", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
 
->>> prompt = "My favourite condiment is"
+prompt = "My favourite condiment is"
 
->>> model_inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
->>> model.to(device)
+model_inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
+model.to(device)
 
->>> generated_ids = model.generate(**model_inputs, max_new_tokens=100, do_sample=True)
->>> tokenizer.batch_decode(generated_ids)[0]
+generated_ids = model.generate(**model_inputs, max_new_tokens=100, do_sample=True)
+tokenizer.batch_decode(generated_ids)[0]
 "My favourite condiment is to (...)"
 ```
 
@@ -142,31 +142,31 @@ As the Mistral model has 7 billion parameters, that would require about 14GB of
 Quantizing a model is as simple as passing a `quantization_config` to the model. Below, we'll leverage the BitsAndyBytes quantization (but refer to [this page](../quantization.md) for other quantization methods):
 
 ```python
->>> import torch
->>> from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
 
->>> # specify how to quantize the model
->>> quantization_config = BitsAndBytesConfig(
-...         load_in_4bit=True,
-...         bnb_4bit_quant_type="nf4",
-...         bnb_4bit_compute_dtype="torch.float16",
-... )
+# specify how to quantize the model
+quantization_config = BitsAndBytesConfig(
+         load_in_4bit=True,
+         bnb_4bit_quant_type="nf4",
+         bnb_4bit_compute_dtype="torch.float16",
+)
 
->>> model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2", quantization_config=True, device_map="auto")
->>> tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
+model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2", quantization_config=True, device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
 
->>> prompt = "My favourite condiment is"
+prompt = "My favourite condiment is"
 
->>> messages = [
-...     {"role": "user", "content": "What is your favourite condiment?"},
-...     {"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
-...     {"role": "user", "content": "Do you have mayonnaise recipes?"}
-... ]
+messages = [
+     {"role": "user", "content": "What is your favourite condiment?"},
+     {"role": "assistant", "content": "Well, I'm quite partial to a good squeeze of fresh lemon juice. It adds just the right amount of zesty flavour to whatever I'm cooking up in the kitchen!"},
+    {"role": "user", "content": "Do you have mayonnaise recipes?"}
+]
 
->>> model_inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
+model_inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda")
 
->>> generated_ids = model.generate(model_inputs, max_new_tokens=100, do_sample=True)
->>> tokenizer.batch_decode(generated_ids)[0]
+generated_ids = model.generate(model_inputs, max_new_tokens=100, do_sample=True)
+tokenizer.batch_decode(generated_ids)[0]
 "The expected output"
 ```
 
diff --git a/src/transformers/models/idefics2/Fine_tune_Donut_on_a_custom_dataset_(CORD)_with_PyTorch_Lightning.ipynb b/src/transformers/models/idefics2/Fine_tune_Donut_on_a_custom_dataset_(CORD)_with_PyTorch_Lightning.ipynb
new file mode 100644
index 00000000000000..439ced746b70f1
--- /dev/null
+++ b/src/transformers/models/idefics2/Fine_tune_Donut_on_a_custom_dataset_(CORD)_with_PyTorch_Lightning.ipynb
@@ -0,0 +1,22471 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "view-in-github"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/Donut/CORD/Fine_tune_Donut_on_a_custom_dataset_(CORD)_with_PyTorch_Lightning.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "DNMqJ821yNVo"
+      },
+      "source": [
+        "## Set-up environment\n",
+        "\n",
+        "First, let's install the relevant libraries:\n",
+        "* 🤗 Transformers, for the model\n",
+        "* 🤗 Datasets, for loading + processing the data\n",
+        "* PyTorch Lightning, for training the model \n",
+        "* Weights and Biases, for logging metrics during training\n",
+        "* Sentencepiece, used for tokenization.\n",
+        "\n",
+        "We'll use PyTorch Lightning for training here, but note that this is optional, you can of course also just train in native PyTorch or use 🤗 Accelerate, or the 🤗 Trainer."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "kWYic8VNyDNU"
+      },
+      "source": [
+        "## Load dataset\n",
+        "\n",
+        "Next, let's load the dataset from the [hub](https://huggingface.co/datasets/naver-clova-ix/cord-v2). The dataset consists of (image, JSON) pairs. Note that it doesn't have to be JSON, it could also be JSON lines, plain text, etc. "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 524,
+          "referenced_widgets": [
+            "9b0fe2691d7041fe8841d87beed2bf7b",
+            "f0d43f6407674c12b85a6292284b4ba4",
+            "99bcc899c1d54ea6b6a95fdda3d4e54f",
+            "9c138abac1894ebebb334b8044ee6ca9",
+            "26bb592b09c94ba081cd1f913c318f73",
+            "6412ab45ef6c45fd88462f76731675f9",
+            "f09e42ab2e9f4560aa68de42fbc4d4e2",
+            "cbf0235e60724033a400c2cb38b3971a",
+            "90d6691af3fd49899b196ff7337d71b3",
+            "9aaff87ef6bf4f71b67dc13553aa73b2",
+            "4ebee50caff240aea9377fa4a2d0d7cf",
+            "5e592f3705ce411dbfccc726d2348933",
+            "749592c5ae004de4a5f31bab3c2d31f3",
+            "548572561a0045b485ef9dde63326446",
+            "674e652801844a33ba01395ebdb40263",
+            "d06409a05ec640f9a6a87a8925dd23c1",
+            "fe66b6883afa471eb687430534bd0820",
+            "2b8a201c62c241a89625630f550f6c02",
+            "e30df53a96fc474da072e8692a0d1d58",
+            "8c3fc7e7b9354d0fb59602100bc5ab1f",
+            "835bd092bfb64a47b104d20092d61a14",
+            "91d8224cea5940bb9858f43b42869729",
+            "0459618abd954a9a95c3eb137954523c",
+            "5947ad0e06a54e38b8d09d160bffb0d2",
+            "5cc9c7f2db1846b6905452d7a9568919",
+            "dd0b6870c8b6435691009ca66fa71b09",
+            "c663b10ffce1432c89a3948e324571b0",
+            "ebeb73a097574a8597d3592329674e44",
+            "81255865450c47ea8a9de6b7996514a3",
+            "507d4fec2b8847d79a884853b4d81dad",
+            "ef6284ce29684d8b9b16875076cd579f",
+            "eee6b3f385774227b35fc4d83eb0171f",
+            "f20da578968f43c3ac44efa032dbd6e2",
+            "ad251dd399bf4671978561773be7da7a",
+            "1d3f96ad71b74c31b18b50d0dafefb6e",
+            "6ff5e86e93914a9ab2ac20d2a32a206e",
+            "986ff3190ef14c5c907d83383571f267",
+            "4c06e9c680b6471c8305042a7e3757e3",
+            "fe170e9c276f49b6927ffcbf3809de3e",
+            "07acf858ebad4351bfd3cfdb339dddcb",
+            "330b85404fe84761a72a8cbfb696eae1",
+            "8030efae633f4b018e7863f46267e575",
+            "f59a9d0b14c348d6b9c221744c256afc",
+            "4fefc71218894bd4a6b2e95ff3a882e5",
+            "565a3479b2f140c4bdba43ba99d71c2c",
+            "fa5080966e724cf2901654c57dbe8abd",
+            "6394dfa7856b4bf49a9325f22dfe1cc1",
+            "baa432ed76ae437e8946ebe41301453c",
+            "6ce260c95cfa4736a22d77f5faba3888",
+            "cf862b504d86425f886ed6d19b55b05a",
+            "12636a29bb09482693911ac3c6ab429a",
+            "95594c0d3f7d4aafb3f61b21b823b32f",
+            "effb0f0cff3c4cc6a8321d0c411a86f6",
+            "1df30bb3175541a7b7a6541b38d51b89",
+            "e563fc2ca1ef4b668604bea1c50674e2",
+            "90761ecf88ad4a1c8dc190928b48fdba",
+            "f51518a3bf3b4a7582dbe26fca21ca6e",
+            "09c44c23e97c4293bc1d30f234634c42",
+            "561abfbe2ed9405d8bc9c67f3a4c4c8a",
+            "c44ea4249c324b7cbbb69798e034cb85",
+            "54e45826ac5f44d3b315e59391fbc347",
+            "f0b290d10e694b4c86355bdba583261a",
+            "00d41781e51e4adb823c44a68727693a",
+            "d56998a0695e434bb7fe3857f5075083",
+            "259d56ea4f394fe591b26941164dcae9",
+            "31d2bbdfa41b451eb71eba642b3db4e4",
+            "848f3079a55c475f91f8efd0f02d72e3",
+            "1b07db1c1be94ffe98ca2e23ca97e187",
+            "9f4c3f2e2b17443b9f104bf7e1bc80ea",
+            "67446ba01e9c4922b041e4ef36ff8774",
+            "5253bf28cfe948fd8520b5aefd5cdeff",
+            "ed76219299d54f908eff9c9678e1e00f",
+            "76839f93896d43dabcb10f14b031c037",
+            "d75985c018114da8943c9bad0c61869b",
+            "fc88c486f35747cd8a3e0eeaf67ebfb6",
+            "33a65dc99580418cb494e29ae5a0fb9a",
+            "c419e4cb99994a5bb0cbccca9c0bc5c6",
+            "d643c6ffb4964990899a47cc02a63b9d",
+            "04fa08f418e74bfe8d274620cd07e448",
+            "ae8b189059e94a7ab73fb256432c18df",
+            "5915cae6f7ba4d5caa52ff5c8f854b38",
+            "3db9e9823c2d4f418cd6707058ff07ba",
+            "d1837ece0226413489f3df0dfd7f3279",
+            "b0095f1cb2364fc991f05f312656947f",
+            "0098775e311344f681335445edadd72f",
+            "632cbce9ea2f4cc5a87028463a877a5c",
+            "487685e439f647efbc2350f87ae5d275",
+            "ca6fcf9c01fe4f2db382b6b0f8cb169d",
+            "15f7ce33a6304293939d23084881a33e",
+            "414f4fac280c49db98080b31e3facc69",
+            "3752aef8ee5147e2b603a691f233cc24",
+            "45ce4745da5840a090620d59ce4eb1e5",
+            "c3f54d242da14b689f6e213867b81cec",
+            "ba402e291fd94f8ab8f1a74c5c1ac551",
+            "fe92ba127a624524bfe051a6040b4c45",
+            "618716c2a7dc4557873d08a9ea2b0b22",
+            "663d883b5cbf4a6998db3319c55ee3d8",
+            "337672b1b8894951810dc1c645f66dbd",
+            "2b1ecdea6e49453588fdca19fc19eaaf",
+            "f2d79a145b3c45389a473ae2fb94e0fc",
+            "e347c9815ff64f93884e65d882c8dc64",
+            "df11ed2a5b2f4264b82cfd95724e7a32",
+            "35560ff2bef140aea29689440aa8f741",
+            "36c149d0545d43d7ac1cb34f4e3c33bd",
+            "293e17ab3b4a462ba7d4adc2de35aa05",
+            "36c215478b2f415e904a24de4b91d9d7",
+            "dcaa8093d0194d76871523cd07347bd6",
+            "8544e6360d83437cb03e028051e96be4",
+            "f794d85eed554a6ea4dabf8420da0160",
+            "f6679d2887ae4c759e6fe58b01a9d546",
+            "24d1c38ed9e241c2b13abd30ead9a8de",
+            "eb5f6ef011b44f7d8a62a35ee66899db",
+            "0bb2e5d6e3544a44940c79b7a5543407",
+            "5517cbf80d8b448d9a511070dfb4dc1d",
+            "107117ee9e3947058cf7586eba69cf6e",
+            "61223d9e086a42ab94927964a4455894",
+            "aeccbc9b9c3e4038874656c34f12d9f4",
+            "8eda879a6d224fb091f538c2806d7890",
+            "c34474a8f453410f8f3dc39c835e3a2d",
+            "1a457a54c55f4aab95a9c3cfaa2a23b5",
+            "fe52a9c056f843068d5588e488f490db",
+            "fee13e5677e84373a18a0f68feb13ab5",
+            "7982ba1cd95e4347ad3fca29f38d0638",
+            "f75aeb7b8cc74ef488ac24f02b208535",
+            "008e77e9b3cb4cc4b37e875cab3f3d6c",
+            "e0da7e4a45a846c0ac14269e5bbb77f8",
+            "3c7e904af22f42dca56b6421d35412ff",
+            "efb2989e68d844bb875fbdbd5c79d780",
+            "d5667dae1b4d479db3745879a34b9ab5",
+            "0fb032afb0904c358aaa984c8556d0c8",
+            "7d77a9f92e984ac7b9350addc57cb577",
+            "2d476a17141343508bcac54393555e9b",
+            "012b26d0aed048628e59dbb0c02f76e0",
+            "b132e3a6f07e452382eadbedff054b94",
+            "3920ef1a0817495696b874cc61516d7b",
+            "24d17f7c48fb4d41b02ec4731d629758",
+            "d91e67e21bfa49888bf6316c154bcf77",
+            "bd0e4a5ac7b5440a8b403a36fdaae181",
+            "fd3d2e91c7a64c2782727d2c29020fbc",
+            "be37899db94d4c15b8e194c03b057a45",
+            "4ec3f7acd47c476fbf7e030426c51a7a",
+            "3335761da6f84b2bb970a32f27f5abc4",
+            "69f55ea05abe4ca9b21135169edc7a71",
+            "d494ec40fa104f16ace482fa5738e771",
+            "ba77336ed8a64ce1b7b3a561844b53ef",
+            "02700c32e4d64a66818ac92209384b14",
+            "9e5bbac1661d4385b06a3caa40cfce63",
+            "bf2d692c9fd24236a6a760a293cb5a13",
+            "ee9f3bdcf3814bbbac4e053b4c169704",
+            "cebe7c4bb7e447949431cf58deedef30",
+            "2d4f64a23cc846a48f0906c74d1502b9",
+            "c6e2d6abd785494ca143b5978811c326",
+            "a867c537beb34cdf905e80246d31dd97",
+            "ab41966250404933aea9736461583520",
+            "f5449d2c5013488ab7396dc95604be0b",
+            "1105d8a1da0146e0963254b901f6fd80",
+            "c61132d2ccbb404ea969d7701fbc3ed7",
+            "45684f2d86954453b3f7059f847028c4",
+            "053e5fb5ff954b1bb8099c07ad77c35d",
+            "439674cf49124161b3783a681b407ed2",
+            "10153cc99ab24f089bc2c964eb5f4806",
+            "1355cef1e865410182443c3b8ba73fd2",
+            "ef4bc97031ee4e798ec0ccb3c1b76e2c",
+            "cc2651a0102d49c7b6a9ac6e82db8c9a",
+            "3a78f6a7e4814c23b19458c6f2857754"
+          ]
+        },
+        "id": "5hU27XC2yEot",
+        "outputId": "c544eb62-6501-4733-a939-3df24824cdf7"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/home/niels/python_projects/transformers/env/lib/python3.8/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+            "  from .autonotebook import tqdm as notebook_tqdm\n"
+          ]
+        }
+      ],
+      "source": [
+        "from datasets import load_dataset\n",
+        "\n",
+        "dataset = load_dataset(\"naver-clova-ix/cord-v2\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "1DYk7tDBy-ys",
+        "outputId": "154174a2-1bf1-4dcc-efc8-7f27f9e72874"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "DatasetDict({\n",
+              "    train: Dataset({\n",
+              "        features: ['image', 'ground_truth'],\n",
+              "        num_rows: 800\n",
+              "    })\n",
+              "    validation: Dataset({\n",
+              "        features: ['image', 'ground_truth'],\n",
+              "        num_rows: 100\n",
+              "    })\n",
+              "    test: Dataset({\n",
+              "        features: ['image', 'ground_truth'],\n",
+              "        num_rows: 100\n",
+              "    })\n",
+              "})"
+            ]
+          },
+          "execution_count": 2,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "dataset"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "-kFsrrh3jObj"
+      },
+      "source": [
+        "Let's take a look at the first training example:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 405
+        },
+        "id": "nHVKQMQvy_uU",
+        "outputId": "8364f84e-e909-4015-cc28-6445eb97dfbb"
+      },
+      "outputs": [
+        {
+          "data": {
+            "image/jpeg": "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",
+            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQMAAAGECAIAAAC9BtL8AAEAAElEQVR4AYT9aZNkS5rfh8WWERkZkftSe9WtuvvSt/v29DI9g5kBwTFBMpGiGWkywoxv9Cn0cfRGklEGASRICBA4RoDEoGemZ+np/W6175X7vmdG6Pf7+4msuj0D6mTViXP8uD/+7P74cvzU/6//zf+5XmsMBoPz87NXmxu//vLLW9euX5pf7I53Ou0O59ZYq16vnZydHZ6fff34+Y//+qe1emOs2Zqdnry8uNgZb2/vbK6sbZyenu0dHB+fndZrtbFmvT3WbjaaAG02641ardFo3nnr5sfv3JnpT/a6E2PtVrfb40GzUR8Mh/XG8OXL1e3NnaWFxfHxsfFevzU2Nt7tNOr1RqNxcnZ6cnz49MGDs7NBtzfZajUpMhwMFhcuD2vkqA/PzxsAajSHtUFKNJrNpk+ouAYMzv7naDZb5KkNuawDo1au6vVmqwkTuBUceYFLwWaDm/MhMANgQKkh+ORm6E+DWmq1wdASEGMpUKNmntWHA+/rHGYCMmePYT3VBwtQ5JastToI1GvD82QTBLdgyOElXEqtXHvLNQwYUuEQsmGuFXor+amNG+kXNgwuGFituEEYHBsMB4UW6k5lA6pPJWZSJGBh/edhirfDAeiZZxAy2+Od/+nf/fv/7l/+q874OFDBpNWC80BtoDOtRuv8/DxVAg9GDs9Oz8/Ozqx5eE4SKgdx8EPmg4GIUsP52fnZyfERJdCZk9PT84GomldiJZNTc2zsH/7oB5+9/8Hk1FSj1QQI2ToTE7/8+S+ev3j5g+9/f2FhHjTQQJ5xFo2axKytr3e6nfmZeeqJYtfb7THwHJwPW9BArgaCqDUmOl3YtrO/P9WfpMKzYX1jb29QHx4fH0P88dlgY3cbToAY5fYODx8+e3p0fIKmnolxRK+C1E/PBmdnx9DSHvMemTVb9TaGNd5BF4EsO2oDEYVjA5RiODM9c7h/cg4vKB8RpCDIq4hQOzbePtzaHzs9g0LMloKKFMGDD9fwEmNAObUCpQHro0XVj6yoNUBRDUVD8gzuJqfKU9RJ7FEDJQNSIClMeTgYaCL89wnPcvbCS/hRq6ElyVw9AYhAk5WnyQooUsVMPFRiyE2OYkbg4x0VwpOQRnUkonqALrioruCDvCCB0uGe2FtMO4gRSAO0kAdY4iVdnD0o7c9rq1WelMQoSw4lmSyCoqzoBh/tFmQG5D3n5/z86pWrs7OzzdaYolR3ZRKKRSl85VhrzFoGIkBuXdBwiDGcnavZoICX1HQlYoAaAZALlGmA+Z2RN0jwWO3nX8Vo7vBP29vbR0eH4xNdhAp6m9vb5+uba1vbD5+++Oijw+mZwUR3DDDWM8QdW0vBcW9nb3Z2HlqpjXQygB46qr+nRqupaR+tsfby5k59rHN8erqyvrmxvX18dqZgop3QUtTh8PiE+jFuGQyk8CvikJtwhGv8QmdsDJgyjuPsHJdRPKjqgIyVOvBQg/r4+PhEr3N6ejzRGwf5QbglbqqKhorFH69sjWOqOiRMBn9MvZKIleZSswJPhSUTK8HGIYEUKeQCojkiFFLEI2inoFZHafyf9KaIQAAWghoCHaLBpEmkTEtFMEVauPGJBaHK4j61QnCkEAdwSeNCJFI9dZUCqrwH5wK4ctYlLxA5eABQmY1XRS9lRRgEWgCNhZtGDg9sXkPALCweXMRBFeNJAyYUDH0mVuQODlwLIdfiEsdRAQAJ+JPi54O5mRmMYWdnl5BBEdM4yx1pQ8+4hG8oT7M5htMiugDifrO5s7tLOvWRfzA8HRyfn5wc12u4NdxU4VDQ9wQMKJM8bsQxomi320fHp2tbW9sHexs7exubW8ur669WV4+Oj2HQ85evFhYXer3u+ekJGFAI8gpPsb2jQyzoqNtpR0lqNActDKI5bI0EI9+JSbr9/sN7j56vb+HrsdCCSCGuSFcdCdsBml8lhdxVBrEtByTr62kcavXzqd44Gotun56ethutZJTLirOtZySlMcTvNw+OT0gXjNwM9eqXGQbnZ+sbK93eRLs2RgPUGKMtxoxl+phRilwPLaUsCcD1kOlKNsiFqYVkzIlHQlBeCMEi6lChR4IiAZ+Sp2gwjxWVD2lQeWBCNAhRB1GaJrHVE9vOWiyQKxA6bWEAEBgIGvmHF6TKbGBaA4/kw+gvaJqURKVqdBGq6k2dbp6o4cKUhlFmqyhqJALR6QJGPahYEnAaBffwCsyDUoEZJwhu0f6AVTWBSXDVxHNubm7u7R/YaMt/XL5tIxpOCEBcg98S92jk6cnJ2Bi56p12+/Ts7ITQ5+wMhOEVyNCW1M+BcC4iMi3oxKcrCQUo/uhsp0MwVlvd2PrJz399RuRMIzMYHB+fHB4fUQiR3H/8+JOPPiCQkdmFlcCT3bX2eLc1hpYdj7WaIaFeP4M4wqe6yqSqDBtEQc3GcGZm9ujsLiTAHloTuFEpVPyPYIMR6aIqD8NYagKY1/DIBz7yCb9UWTs7Odve2jk8POl1JuSO6ckDhYpqYNvRGd9Z25iFm4Mz2ibdPsokOOpCNvXd/X1oPqfJs9UbpD1Q6o0WbAoanuAqblCsSaRsWEF+6yQVuhEGmWJHphFNqdDkLCoo+iluQoHLuRArOA/CCVqe86KMVU0VzWbhMkzlEtTSekawPhKDwiVNjVYiGqluBQ5Zwkuw5F7ig4JQS45izJKdjKmMWko2fkA0WAaifMmdpVV+EQh8Sfbw1sJhtEnhRKAGJfModDlCcfEhh4E+ALvjXUoSHeOoTmidhrXT83NkR6R0dnCEiaZpx+3CqSFSIkyYIJ5pNlr1sc3NbR4g4QgPuAQqaZNVOe64tVdm5marPTbGU5Jx1vZBZE5t//AQ/hBsYAzYFUyXjNrw+asXO3s7ExPjrXq8PeUIw6R9SGPSneiC1cnpyVizSaNEEeQIEi2eSz1/8rA5Nz3V7YzTB0gapQu/kimKFWZFQkmLsQlBJCREyaFRVIZ5Dmvn7bGhqtZsnhyf7h/sz/T7MIgQET6aXodB4EDThDG0dnZ2jo8XOm2Q7IAfGYK/cSTyIoKiGsNMZZLub4wuIrrA0wsYFM9YFFy9LIlcRKPj+iOCPJIw4naB5qC4lKCy1Cc0CCtP+LGjkfrVUijwufSrGXl65g3670lMrMKOsXCSBa8rygK3qEeBLxxSKGcN4lBaTOCKg2LWhcYGwgMAmAnqhAgQkAaAZQtQknBqgR57JNVsnGOjopcDR44sMPALrLBfqyWxZOCJII34ww1rqdEsk7h7cNBUOVFa46vj0xNbA9sDUJMEdAH8Udj9swNgLi3MT0z0lmbn9g8OltdW9w8PUFi4QU78Le5PUPQn0aKzM5BHfYvq6xnTS9QdEoDhFmkUznGPokSKSttobu/tPV9evrS4QP/SbLXzquGF8Aa21MJwjk9pCcaN3BrDs/PTVmMMCtDSFrDAptasTfV7U/3+3v6+rXzMoPARUqyocLHSv5IQceJkVRFSFCr/FBTBVaMFEw6PjtWTs7Od3b1Lc/NU3B5SIxJF0QGJolgIRT86Odrb3+2Njw/aFD/D/ItkIRlWSgNuJPJp2Brb6YE4Ho3qrXQiyOonQVr4ykSpWJn4SgelcmF6tCfYj0g2R+GthbjmqUogo+KQSEMw5KEKnSoI5prMXmAkKWLt5aD2gc0DPgyvJshycEFxKwdLqxQb78is6wVxb1JgBM0AhrQIxfIjaAVoyezT6j4AycRhYkmFJESg+7NCuGFVGo4Zkqfk43lBNFRZGRckkb/JIMjly5cfPXsG/vjX4zygAHInH/ZQvJZk1Yc42bdv3nr/vbdvXb82OzNNDIAlfP3g0T/7H//lweHBOP4Px2+bDysVDhaBSsQqyuCPaPBUftH70NjO0dJWvdU2ghjsHx1iOSB3dj589OTZpx98yBgmvVPF27R5CX02NXRsZuemAUAVOqeBQym0PPwR06vLgB9vteZnpp6/eqVIQnt4JzMKywpfRpwSZ/gmjmqbWkHGkgg1tlzHUVX61rXa9u4evW9GvMiDOTdbE1RpXCt3B5A9ToC0s7swOwd2KlzxjcPh6ckpGQBHb2d8vAuvsPLi1YKXIgQIR7DVvQV/9V5UjVAGxF/iGa1KNrInoZwsDSX+ceSRJUNRpR+USuekREcQrPL4DFXigj5fCtsWjgqGCee06WIWhVAkPBeuWkgRnhCaWhbnWRyz0IDRNISmZxu64hfLYE4MngIFy6o6S8hMhxO4yv9ypfYXWmAU6fI/uQUvBvWYtAQJs4Kq+M2VlKCfMmbiQdSKU6/bRTqgDWhEhoIy7kO8RD1UA2lIcXKy9947t7/10Yfv3bmNF+h2O3ZSG412Z/L7n32LMfJ/9W/+BBVGrNSVvoSdQERWKizaDyiq1URyxp96j2RxtQcHcA7fDxboOwMzyyuru7s72E1LM2nVTk+JODBegdfrL1+96k9OnLZODTpsB9NvpijgbHYU1LDTql2an6Nxkh8j1hSEUm9oU5T+IcSKLfzaX+KOUhaFtb3xLkNs1y9fhlTSXi0vn9BFMmyyIHTCObud8ITC58xCtBbmF169euEw09lZo06XC2DhJzylrmbt6JjQcFYWWQl063GpmAv5kpTIXUmTJSbiBTQXqdPwSg6StZ3hCljk4j4EhRlmEKpnHoEqBxBKLaTDM6mFPwoLo1RRZBmZeWKFNjUykMctYj/1QmUXI+nPIxwQzSY3JlGX5Xgm8DRiXNFsOt4qWGvyeXIK2IukiH85oErgOUgRZnDjApghFl9OulRzXxWTfJPziGSylmwFggZTygs4Yi4AGSxfXFiALSoEDoswA9Vrdlrj8IoofLC3v4dZLC3Of+vD925du0oVeDswYUIAVAmakduPfvg7OLh/+6c/hhrG2ell6NrpuQI2fDY0FrxoIARueUI8dnSIl1V42gTjH+TWg8Dm4f7e/vr6Jg1Th5FICvIMPlNZIqpnz18sXZqnP8PQppF73XEjR/cLXzDeMbIPGrNT0+PtsZMzw5ARV+UAFXEru0xFMdUCZVEeQV69hjniZXrj7Xdv3rxz/caN61d6Ex2Ywljxr37z+avlFXoqtEe2P7jQRovOsaAwTKhotaampx89enh0jOOfoK0iHegJBDENx9oGwzGsBHE7gAD/jZXsFkWiekqR81/cs3evSZCzYK5uhIqMGFh1MZ3KufuYYqE3P7lnOg9mkTMEN7mCcBouRyM1CGUTZlhQkeQmVFodleL1OfPntAdVgCzu3iCHv2QXkPoXQJbiIizWR1EDUKiW0oqanEHMehzGMaoOegUAl7lL3QUkZ5DEaZQHnEt68BMBbpNYwUk2UZPoHKRwLQj7b3leq83Pzxthg7VMZ87LGSp4isDI0umMNTqdw4MjDIT6Gkb/OgPcH2SgGFLUbP0nf/QHa2sbdx8+pLie0c4AVsZYI76zOKx4e7TLkGLAiBFaZE/8TG2iaoDDB/jFD7yh97CxsTXV6ci1c3puPDnD3ZO+f7i7ubP94NHTmelZhn7xv7Q5dEzjrhRMiWzsSk+ght3u8c4OiFJxaJQTcgEx223xTOOGUpLqLIEWjO8z1Do/Pb9x+fK33n//0sxsd2LcYQIamkHr9vWre7s7YA+bhEVorekb9VzoTr/fI+Xw8LA7ftxu02m2vWNUmDnmsOb8+OxADzGsddrjugM7M/FXuGSC7wg+eMoQdQoRoWBFIQCtvIqCcQYOOlQuirQVtc9TzKJRDkglyewcKjqKCLs0Qm7Bn9EN5Bt9rfKJCXACK8QGYrqbqYm8pRILoRnC0apsIHxibWp8apXAWBfoAMxzsoRztKe2hyJnGf5LOJlMNF+V2WuOZONXeIEmvSSSfwSzVDDKGHRSheBkVwogF0s1ml2i1e44GKMtQYQCSBZx0SQ4JkO0sb27/fT5s5vXr5EDzW0124zo4/7JghmgY51W63uffXrv8aPp6WnQZnKNDJgBKOnmaHozkIgDVSJQQS+csVPiwNxKc0WCiMjFen1vb2f/oEeAWTuqb+8d4Dk2t7ZfvFphdPXl6vrxyemnH31k49N2gpwOeOvwlOm9o5jW4Ohof/fg8OjcRmrswHkQbDu8FbRcQDhwln+q8znMA9GSQVwgv3ZOkzM7PcsA1NiYcQgZ4BE6s7g4f2P32vGJClT8AobEwBHhIUYk44d1RuXwAHQn+hP9s/EuJDVrDczgcG+b81h7bG/7ALuQvaBvwEOnx6YDVMWL1NEBslR6kRJJk4HHJa+ZqdR6U7Dk5FwuzDd6WkCWJ5GFUIzoVGK5XlR5xBoq4EGK4/UlNlW+gZsAAeTZ2q1HGCSAcNIq7M0GV3lIFvMRKaEWZARqDjiQ+lNakJJcoJaLcn1h8I6OBJaIedjqlML61NeHYuVp4VvJM8o24hiPB+fzszML83OMF4EofwTroEAvgckaumWoGgSh659/8dV3v/0d+oHYx1kND4hfP80wkbXgxudmp7udDjPH9MLRMhqDYwdamOPSweK2j06OiZrVMDQGd1qctOOI4WG4T/cDHNS91tizV68OTw7Rxr39w/XtXQAeHBzsHTCZ4Pgpozirm5u3p6bgLWQDsvWv/8NfbO3uEqhRq3Zsb9+BECoL/ZU+yfnIPH4wPgUNp1VGF5h2wCzOTqGHLrzz5mcM+2BIKaT7IeOw0e0uLC4uv1yNt3Ay8vzkrNUdo5XAEqyO1RkMILQ7r5ZXF2fnTvQKJ2PjzeOjw/39nc2tTYkf1pj8diUUIKsISLSCKmc1Bk0gIx6KdG6TAnEcFffAnsRSpDxVs9QhVVrrshFQUS7Kcs1hrdHxokXe6Brkm1QKgzszUjA1mBGhJdUHQraZRZtBQMU2yCplrM46cmf93HqjZts8cAVygAj8kmgB2O5D/ot/wdluPPDAMJhw0ndwoO74EMGmshQkpwVjVKkxGSlLeooUmCmfnILhENiA5Wn9Xu98N91apBwOME0FRDIkbjX31s7ek2cvp6enqBpVTvMhVQ6NNBvIlMVLvV5v9dnzVusI5WHR29ERjv98b28/Yrc61AvN1BagQl2AOi2BLhycp0ZCHWL0lqs86hs7+1v7R4QgomKP1DEprn1aq+Hwv7738K0bt4i+6DCT0vry0SM9NJdwGgCcVKZyw6/6Ec9X5ZFCsZJlmGDGvhzuhecnx8dAgTt7B3tMIA7pGzEZnNCiOdaGnn5vcrO9hSzJQyUgQbOKEcMz67Pn0JydmVtZfr69u3t8eDw4P51dmj89Zz1SY3WDYeJD7OXg8HCyR2tD/eAixihbZBbpyh+f8YvA+FfyiLPXRZxmSKlS3DMZIvvSysmOpKh2pRAIB0jULuRzi5aDhIy2LvJGSbyyXlXdczHI9AGSWfKDW3hq+wq+KDkEkV5o8sr6KAAIqybTyJFbj4or4nTO1PL8Cw7WXpAODpU2+0gAQVCkXvcuSlpVhJtyX+rlGsjWHgbmoaVLMmSg0xMTE6w9IwP+lFYgho/SWIQlSuRV4PXBvQcP3r1zh9gFtWEdGjyg04CmQjY5ibFZmuncM07x8BC3jfQJ608JIpj1RQWd+2Kss4luw49MxCELbQ06Gf8co69u7E6KJ6mgjaKbQQZ86gnLhmgYMIc01MPhw8fPsQd4B/9wq86IGFpBWYiWSkiv5FE4XCyFZA+yqvfoNzc2f7KA/qu8cbjgDHfHvMH+0dHUxASjJuSUztYYDQXzi4yUIkL1ADYhfHjB40ptVZuZmZm7d79C69dOT1+uLO/83EUfdpxOGYan+ubswcHkRC/2JbH8D+6VpMUptlzRkacmvqaPx7phNct0ClK9eJpJ+iSlHJa2oHmSuRANRag1xVRAkBdQlNbr5Cws9UZ9VWvRaXpRgCOP7kygajsXyhLm2XmWIWJjIijZMQUBSoBFELCiYnXRtWBKGQ/5rPC9ljCD0gptnwSOmPqfsCdyCTqFETzwz6wSX2i0ulIm8At6elCs32xIllXDnc4RMYXutjk+jlukGT89PDwgQ4dFmM4CnRHhrKyubG3vNOr0YxnZRE0oXWhz2AfjmJ2ZOTw8wpJo7BevXF6cnZ2cnDw4OGJBx5MXz5FMm5Jj7YIgmn1ywrKiGtGT2Kj8cpBr0CuqZRCVJWzhTLDmoXm83tje3N0/6E/gjZuwtPQyeVBAlFqKmakZmomCg8VyibYMNoBo7QxO1sswWLrdA5YeKodMdhDSsXhvcXoKRlFYAwZVKGnX6UMf7NPr9bAXAGTw1ySoBNnXpiYn9o6Pv3z8eHN3d21jCxVos5CPobVm45Cp/POTmZ29K4tLgvOwqEhSA/gZ16o3Cs8UgSpMFU3BlSKRtgLOvarvEWMgjasADsVegRvJ6lkAluocWhVCAvcUMYN5/E/lqmuqBYL9XeoLtoFOFvAxX0CaU1PhJkcBJHAbdwiD2MIhQZIvSg+CBoiizwVluPKp2pXaQhdQyCIschWelXypmyxyb1SxOQUjLvwW2YUjirDAgbYACCE1ApLmWIelEKyIbLLkgSU9SKQz1ulOTBDUYgOkIDYQYEjw+csXHcYtmfBi2hf4DcZzsHYNDDQuLS2xZP/alUsfvvPuu++8vTg/M94dZ+R9e2v7L/76b3/6i18yKAJq1GJ3oUbM0aHriPlxIA6GasRZV4BW+C+HyEYUMkFKZYUJdJ3pQy/MTDGGaW8EJDjIZD6AhHGqFIX4ATg8kWoMwiz8STYtEF6L+ur0C3DbTpxBMNXTWSImW9/ewh7oeNNK0OsFUXSXf7QJ+7t73JrTpRNnzTEtMgKg8sbU1DSL8e49faY47YdIJ/6GR/yB3+HRCaoB7iHKB1HWogQISbaCLanRYa4K5dJAZqgClLzSb6sFjr3xCCqj3HIuqiF8//KPC92tWICYtNPGqjJqDcQUuzM/h75DkF5bu/GRlXpE/YWZmzwWJy78KfAgSuCZabKU8KhP6+EmRQNWaFU5G43yoAgL1aKIdYyONHpQKv6ULkWJbmxjSv1BhjIph0yKAatbWrKeQlrEsxiDNaEJmGNzZXUdVxWdJNwgO8l1lJi6UA+l7Bq24atXy7euXqFGAmMaCwYxXfcW4EgL1f/RZ996/913b9++QyVkAFJvvDWxMPaP/9E/nJ6a/l9//Gd7B3aCWX/RaU8EE90/4+xQp/qBtKoFzVqCpMs4TZqnPBN/9QpWo5PDjc2Ng8U50EV8vlQhKuWopEcBw7iiHYFX2Cwj6BtTH00YIRcYGLcQIDHODxusQEmjuVubWAKDvvXBWWVUaRYajM9WpDvswwJVbCAyswsvGgxbMcqUYTi5DsDzc4eVMS9YABPgK43eESujIhv8HFxQOqGbUwopW+CV9FEGa8aKTNQYJJCeq0oK5iQDi983CQ7QIOysNocloxB5wiltjUbKoZ/XvJS6dXDIsGJ7EQp38DVmCiZiSL3ceukBfFU/B7cl3TseRUReAZFHEg17Qmhgc+k/yXLOeIQA9+a3L5HLKHSeFjhCESgHMkcIguaMMod9+iMj65GSpC5VypoE3ZifmVP/HMw4290/3Nk9WF1e393eZXQVpehPTHQ6HTPW6itra6E90Yvd5QpIMGhMTfZvXL22tHQJrWUtBhDREApiYSyi/ge/94N//Md/bDsw1obDrErmwJUrFJd48laDdo5hSgp8zcEEBYNV9rV57KC8CkpLK77DAetXT494u+yE0UmHLy+IpNqwLe5SJOWVP4VmmURjUeRoCIIwAHjGcOoZLNgnq+aJpdRqOzt7mO/CDApMa9CCU7gOKnf2u0XgiKqfdupd1FxGY67ymnKEfY1LCwuyRo0LQqgprPPtH1se+j78wy0Q3mWQN8WCZyB4G+kCwTgb4qNGBX6EpwB0oiBPzlhGVMravBcPaufsvermDwkhHWaE0WYSTlAVrkwmX8FHwVuczDzy4NdLM9DSEh2MIGodwkznO7UlZzTdgiXYA6zAAFGqKEIBrUIFUGNSPC51VdlG+FgO3YjDNOIq6Kjr1Q31kBhtiJtAdRyw9SmHapCyYmBiXIcP6jqvw/2j1jir4xvtVnN2evqT9z4kyLl27Qpj3+32+JOnz/70L37y4MnTF69e8WoXPttJpUBkgEKShFPrYzpdFhrpc8I2q+EaZ8GgEGP+P/yd7969f/+r+w/brTbDTePtNm6YrgWecsQEVjrZJw47US5QPj/VEoRXeT+wj3BxynQ2Xq6svFhdWdveNkDiAdqV1VLyQtrR8zSvYQNcANNwGJTz3F9YY1RMfEQbydJyBNki0sD2+GNNFSMJIuIrf4kfogf0ren3nB4dWZjF4TQKafybNdAAKBrYnJ+ZhaeFP1QEFQ4QFPdQbzCg4IJ4ZytBssiIXzVSLHWyagxJ6qm4c2ldZs4B5l77wMRK90YPw3w6MI5z8hhdCAiuxCicIN0aKIgSx6RSOOB8ImhrqGrBX8RgwEizs1iI89e8JR/y4bI8ov2EP1XzUvLaVsHoCstQZA1A47+AAocauQitXlJjKZAKuS1Ih3xrBdmQSS6qE93S3qlMAuef4ACU21QE8Aq+z2TsRG+C13nhxNzczEfv3Pnkw/evXr02MzXVZqkPgOr161cv0wf4p//iXzx9+XJre3tpYc6q5af1VCQ4otCamZ1FuSfbkyg068S4ZuIutWgb443hJx9+8NX9B7hbIgX6CBVa+Lw0YHlPLqvU6gOmI6hFHqE/dCQwZLCF/9CY7g2PHjx9wnuXYjCst4jiQEed4Qhakl5xQD6GP/JQAHAk+RL31lkOem3x0tRkb2l+fm93uzfRf76ytsNq0v0DokMWtDqLZkvtsiI4Atm8E4fhn/pSBcy3UryDvMACEIdj+bXJqUnGmPYPj6zdYEPsYUSaFJcq7RzsZxymaICAgWNmKVBf0Cow5kJGx7nLdGkxm6wIubEZE3hINjEpmWAHOW2TEJdOoQpNCiihCAeIYYf1FkWidNUulAeBJg7iH87JBFS8DAqVvMkULAqOoQRAEKC3KE/ohQknt0IQJE+SF7TN7kGJ/MoJc5mcYoYQHiTxrECNfSZJ7KuKtNmIWQ3KnzFfnkeNvLZM4U3e1ZxjkKff293bm+73333rrUtLlwhhIgqXiZq1WXv/3Xf+yX/5X/0//uk/W15Ze+/tO+KHHIwpfAc9OCKCGr3E42NGI60FjShRMU9RDikY1C5fuoQBYCFt1nGw1P/UNxOQI1aE8qTLqj6TwSZM+WXtGsPwTOLaFKBMZK6Pj7EIqHF8wjJQono7S5aXM8UhewHr9K9FS1RELxkMY8S2QZyO56II077cvn3t+qfvv7M4P82SWijDbV9+sfLFvfvpJJ2yqhTbBRQaRiF4jUsEdLfb3d7aAIgU8r4lK+tAEbNu4u9PyDHZn5js9Rk+gyHlRR/QcL1UC9awKHXI20lgD6qqgNpQyTiSVvOBpjKr38QD5JGPoc1rjYNXgPJAAMpZEJzhTq5UDCSuiXmp2ABFHjVMaAxWOFJRPaq4FVwCLiqk+qiwFKOuFC/Vk8/qKG9mf6PLnioJ0AUqrWLBQ4lUT0hIsSpK9Tr/rEoOc5QQyCtryWEhaTRRkCYLyYvkomEng7AsFZZ5XW4FkUSNgmpKUUso2CFhBqN7Z7zWsn9AoYyZsr6aDokLkAiGqRbtwRj+i//s//gXf/kTx1XUigELceCl1YgDGoBWosf0AYmpxvhhXIiFrgQRxDmKplabm8Hqpl4sv0LFURjCY+ghsMEeaCcIm0mnUvCNqfEQvWIJKlEb/WHsAFds5wJ8eEeCkISYBdtjvqGMHWmOyCwaKXlUqo+ONqG+DHeCE6LjBUxZMaR/7Lv687PTC3Mz05OTtD7dXpeVIG93++yHsbL+5/sHdJgdNBgx0TeYqZ/CvLAMfvCLw5fozk/r7QlsQZbZmTlniHd6avLl6gpLzykuauEvlGJaoLGzvRvIrBiBOtyt/QfF6E+RNIYHP0RVR3ChqWbjiKJq8elIKn+yhrKUx4ZKpQHCUzUMZkTTiFcNQK3anoYXujANj8uAz6mqAwwQcjCRkRlhiyKqXOS5UK7gPyKAbIArd0GOp9RHCmX0G+lAk1j0w1QOzkWPKShx5jPd0S0yqN8FQhKrk1j4wBritZJOPss6rpZWEb2Sj1SQ/LIW4Pq4GmvA3KgB7WGE/+v799+6cwtdR5WB5zA/4weK3ZdsP/ngg6++/pqoocML6ahGKzESxhTvRcVoHR0JQKNvAEHXmVzLrDCVw+7z3niH1xseP3sK69gjgOWvZ8dnLFKCPrvFYURxB1hVkMS+AIYbHWOug6oYkkJe9J6J36mCf26ecnLSYq6C8pSJj/UtJOwBufrHgK/00r854/WHwlaeQjQNDFbGNHtvoteyoQGEaoG/v3nj2vtv3/z60ROmmUkhL9AZ9YSlXMIZCHPyAf2lM91hiWKNAWkNr8Y04RjvbtKXWFpc/Pze/YhQC+ftZzDRrHWFQ4aoj095B7xvBv4iO66jrJhrhKh8lR3F08WIGHNVSd4f/VqhSxhkjTKDijxVawJb9Qpwmzc4zp+FvZZujxEO5e6NczTGKkDDIjQPRZc4B1g4LMbccQ5CpXy5Kylc8wxbSkZxthWHZP9rJBaJ2FQnmAk8rNQ8Psg/8qROU3Af3qagvTgISZCgulOq5JPXBodpMKiGR+Jh2yi2Fuc0YMJ0fmFh/8kTRhG/vPfwBz/YH+/o2hgWwRejbAiO3JgSM2PXrl5dXVtdnFuQo7FqnuiEAhbtYtAJBhN9oMpER2BFn4CAAEyiBUNecvj3f/Znx4Oz3vj03NI8jhiF5KWfx0+f8fYc7QNWSXUoGbrmcGNWgMMUQwFg5sUGbrQBKvAVU3dnIXZq0kREQyAbb2dvibEq2AHX4RHU44khMu5HJYDhJE5P8/bBDFXBUmrgzMwAnQKWfL//zq3j48OXa7tMXjDxAhzwo5g+VYVuOCt5eARt0EuNDBbAWfQNOxmc0p42r1y6wpYzpEz3+gzSvfPOO0i235vg5df17c31tTWdoqLgv39FFWJOqhMsrpSjEh5JklOyUkYSLE2aspUm78FPTKIkaoFe1XsLoIUYc2UESeEBj6r8/HL9zQPIowSH5OOYS64CM0VCQslnqgc/Sa3OBcprYCKDDQd1i2gOhd5CS9VSgXzI4hHSAVfvYh42eNBJxEYsoa5DZGgLI1V0LAPmyx5ZHIzklrWEkoIhvUVZwLxvH4dIzFFvsOnJr7/4gjcnWYlNVHPWcoGZzUIOJoEWFxc+//ILfGs8fYFtFZEBIZDvIa4srxBxUYoogyEphurtbygOMg5u37j+wZ236I7/8Ic/vHr5MvtuESDwQsKDh0/+9C//ivc2IdzYn0pllO0MCmh7DF0u9vYgHnIOwB0n3C+LBU0t5gNYNAoGqrhBFiyh56Fjob3Dnni1AqQJ2ihLigLBmAitsA3W21Bi2Gg3XUBE9dQEHBZVwBWWuO7s72HfjOWyNhvgUAILQJS4DUugjggZ/Og2RVp6Opjf4N2O7nh7brL3we07169dX7q0xMAwL8Kycdh4u8noQFHhhPqKR1bmjLDVZ/la/H3F5DhHUhFxdMCnXKkBakkOIQSSyk0aGU03F+k+qTImd04kYj/lvvx8I0uSOFGadA1RMKNzufwGsIsbwUgLP/7/5iGepEJOgNooquXgH2/lBVKwjP4l2pp+f9yunFBoYuPZW/7D+DCMa4qi00BEGaTbCBPphFvM/yQ7OcggHnjAVoMtVbhA5dqNsbv37n//u5/1mQLAEk7dmcrGX2MgQKDLu/SzX/yCoU+CEZSFCAONyUvLAJYAPOnPf/31tevXWKlG0oDeBCSQMzEeBE5OTvzv/uj3+1OTMzNzhCQg2G620NHJb33Y7fX/2//uvz/SaxMPudKOKIOtNGgb9vZ3ME5qhD7el4RMo1zErwvAEjKEjSJiJVgIKh7aCnnGV1wRQrFBDHoPc2kcEhoMCLYODg6/vnt3e3uLVUEAIOCK9dgI9fr9xaVFAjQmGegE+z6hNKuhviEkmqwV0XKcInB2UHQ8zKaxTfcnUXred2PFL++CaOO4HIar28xSj81MTWZ2XDxVidEBgNxKLWm5VgUBK3xkZ+aIn6K0dRDsXAb5K30jF1d24Wm5qNRcOkENNTdi9/ceJfk/8rCUENib6P69cP5uoqRIT369HlUiscWKC9icVSb104rKOUUggwTtwqfQgi5oLKZqUWiHrlBXoQisJVRDbsmYWkXBWiOjmAQptk+sHU6NwBisb2w+efLYcfkBE8y820xHlrlXwZNndmaSIabtrS2VECcqWbgn68PpUP0UXcRXK6xdZW0NKKCXPMF7g3OhBLVcWlro9SdKIETIxMpVfCuW9947d959+w41IlYOtJqohFj68GifuzCLxXg2CCYeHjoxzBI/BvoxfuKiVIG84ZFk4wmIl0Cdg/JkZn0VZMiydPjIwBPeyXy18pLdKHZ3906ODhwYJfH0lGkEUugxMwrAdnoUR60snuDVbjtvanR4hU8nRkXYrKEbLM4B8dhLv9fnpW+Q4zUQznCe7OgmY2fESOw5AJpUBxNloFIb/XiJIP3JEQWOciBtNAcKoVSI6oMX8let0Fr4ByDopCy/CY+IAaxCOSn0Krd5U8wfj5FOJqv3SeVktmQCpppmJRx5kMflsihieZQ8ZktiChcopWCBCZwEMcKoEC5CUzzWz2NOwSNKqBKLiWTpyDNFA51wIVwnpwwKegXHQIBFMIfhCp7QVBR4GAy5Ma/iGZnuBYRdyGS+9/ARlsCfhKDv6csCm8pYfXfz2tWNtXU8rATKJUGiUYqgXgMUZH3x9deoMo/wsSCPspqnsLHB5g9dpgtQJGDT2gCHeiGHYaIb168TO2gH7kTaZE8XOrNHR8e7TH0fMDKfgRzABX/Qoy7UHX/tdC9AUAdFpHKoOvQ1oAubw31TjTy1CZF4Ayl7DrYO+JXVzXXUfXJ3ZpPx5P3D7d0dBhBOj08PaUlOThkl8C3QZh17yEI9qaY4LSO3Mp0FdmPMUO5DicxFV+UMbU5jkTmK/W13RzUki3xQRjd+ojQTzIgHpDiqIZ1RlgBAA1CdXJYf3RFxjoBUWX7x9TBB0esC/C3p5pdDVuZ1ckRigiyKQHYfkBDdqgpXOFro4kjO6g4UINNhIY8KP8DkbnRb7nwuylU9arwF7BvpjLLmXswwTdUFLuRcCgcrMKYwtiCa0TcepoSEh5TkBmx6RE77hIDq3tKVTmjAprKMxjz8WtyC+TVtst8nmS3osBiePXrynJ0mukfdsX4fTXEcCXKIwKNCvNX77OkzXjthcpp08qNfqDE1gCkvKuDy791/+IPvfpteL54Tw0br0GzNDHFjCQzE726jumDTZGcKV17H5IZDJjcwcmJ+vPLZ6RhoH7Bn0fGhrESqGq7KDzR0Go8BS/VvDF2q2LLR9h/SHVXKHguE/ITyEZ6MkBWhmzftAVNYvLl7+NPP7wGRCW9eRgNMe5zFp4KBMCAfaIKuN6R6DuyHngeAMD0Mmi5LWyQMfcJcK1EuEtu4tLh4cLADZpqhrkhnbrtc581Yd0HjisgmvzBIrShH0e/oXJUCEFiQG+DEL1qRMqVdtNxF8cIwHRtUwKw843kpXXighhbtoKh4gW6YQyaBk1rwST7xDPeZUFcjSbQ+CpY/knKIxujwOvTEgM3toSCLeXIlgKR5QoFMqvKlhlIR2AX1ADNdlFjun1/Lp4zlCIrS6FWFq/rDB5SY/IXGqgrvpVS4mvdCFsiwkMYwaFAjKFjf2KAvC+2EKM4W836VC6op0mAqmh18d3d3+5NTeGc8LkJEQEIDWL1xeXHpi7v31jbWOpfpGNOVPWFb3FhUKnVgvMkijoO9/ZnpaSJ2EJAfeJnBcHKK7aVbJ4cHRNRw5JD3MU/OaZ3gBN2YqAHkGPFCioCskSktuipyyjEixnyBSNcWfPr9PsXsFWAXo0EPrhE6xDCJgZJEoQZ7h4wOARZQDBAxTMwG1y6IKO4XHTaIYUhYYzB2YwSVzIw4YYMEkd3zCfrxtEFwBNsAuHokkvWZqRkQBgU62YxIh4mIQ27RLGi4XHvo4fhRObjC55olUn7jxBMfg0RJ5Ndc5LMumGEh/qP/jG5FYDgcPVxVErnHXEpdwhJQMYiigslo5VUVFRKwhgGRqmqhcai0qhcQuAgcGVsQMDF15XGph7TqyL1PxF6ROcgoiNSap1WRcDGgCksslP8xXS7VWWGQiGZQp9srxZAFX2W2muJFqCB1pHJyIuLUSzh9tjg3+1//l/85w6msN3v48MlPfvrTJ4+fvf3WzRJxJJqIYCJABH39xvXnL54RcSF2q+dlz1GvGXVaXJgHHVYrsQJt0B4HMw68SYUAA75jTYIoXvWkmUdBkJ8KjJINh5P9cQb3ecORfUV19M3mwtxcb3wecnk3c3t3H4tyiMhaIRGN990spwWK26N/CMlwlAJYyeEhPQz5i3QM4BAXOpRojDTEn9Adncea5QaFEQm10psxH0dYSXeFgqwTbHQczWBazE0etUWGe5usWyQ8YRiKeAeba/kOk5qcrs45/QF6QbBSb0QtKrHI8kPFWGUqgSBttaDBU674Bz6K2XTylwwi5LNgVm6SvyhkEnzMoVLwA+a5zcmsecrZ3wJopLql3Ovc5uVZzqQGXClhHp7Fy1bVJSnAR+Cs6w2QliwJOedJsChoIsyomnCqoyD+usZRsrYsJWoVrozyaD4y1g6wKm5kK7V49omMR7RSUGoMXYBLDtEhN7edTuvjD97BGzKo8d7bbzHj9eIlm/rYMZ3oTqBBOC4UKTE94mBHjNmV5ZcMtdPxozQQdA9hCI0KvWqakS+/vP/pRx+zywqNCRCIk8AnY1CiRv+Y7DQ1mBCyFmdDrDozu7O9yb3e5Ltvv82W7zPTUzeuX52emjo+PNja2nr49OXdR49X19eIR9AiDYGDwvZl3bCSG3ecpL8LTjCD3oyaZABZCYXcun7uLKckFYNz3RSFifAAC+JFbCFgE2mq7RDv7e1xhlwAosq+NeqkhlMUbl7E+89nLKVydo9/ZAlWNIJnjAd0x8eY/QO6PAIXJUaTYnuAKVI9dan2IskNZQuKEZMZAFrJNVyODlWlyrXlR8ebKZTL1p9V5pS2FsmW/mBDweryDRBwxnQf+TR3FhFS2Bm0TS4PYWUwT+434FSXyUjZKrO5CthcjQgclfuP/EaKQUD0wxPughU4xS7gadEnMQY2kOQuV2Q3Wo18kqyRWHuhLdkTTTgA2kYEc/Ozv/d7v/uv/79/srGxwdJp8hGzj7lfenlLQSQZmp/odenC8kGMCL3YoPKiRlZpsvCMhassUmKVGiGAIb/7IGW0HXxQBXrDLCY9PWPLX3BFlSmLItOF+NH3vvfph+988P77vAl8dHRANqatHOG8cf3dd969/fD+P////Juzw8zTQbzdgSG74KvXYMZMG2/707vlH6vM3UFDCQGfpwZVTNxhKpwM/7EKMbERoCUgnWQuyUoLJdd8t5ZoCwRra5uMEjCOS4UOh2H5tj669wEVstOx3XibnRwU8TWgRFDsxjc7z/wH1QVLAeOdyg2aCgpRJymQgSBVhCOrrcKfHN6+PrgWwyQqUS5kf5XBR7k13Vy/dSR/BcEs/o2O18kplNKBIRu9K/C+CTblq2c8Kf8sH+ijIiZ4lMRcgqVVY/A6l9HT/P7dE4o/SuQC9bcJ8Aj2pdUtGSocC1XkMVvYW1hUUUJe7wvQDDTHsvRTaMH1Kzfevn1nY20DLSe4ILzgQt/qYd2oE9sNsdkErQZBATkgBtFzhSqCLK+88V2auw8e6pSxRf6Xpowfuyhq2nh7nKdRGfFABVEJdPHdd25/+N77RvgNFrmNO1Tjq38oaKvT7b37zju3blyjRlECqhGK/UxmvFTKMEqieSB7VC3XX3iNOhv6yOsqJs9jnYp6bYgGLD2KgU0qqLr5lKi9ePVi7/ZbmDVca3UdpT9hlCsTEIy0snt2f1K3w0FDQd38C8cwwubU1BTMcsRC66lwA2ErMWjEB5AdTMVSfBQDt9Fk80tIKNJhiM03DyHm4Cnw+V/AQJS3FJEVSSz5quvixwM+FYiCj6qU3FQn0RqBqfIko9nfQAk+C6PEYxXWakxBv4J1wQHSi2j8VYoU5pRsVZlRkb/7qziTGQLpCsExFV0QoRgdEJj3QCxQg4gZrCNMVjm9L/8BKfYEuseMiaMUiPmtWzd/+cufM0DEW4qM9eFcWfpWVEXSeZ2Zzu7Tp7t7u2yEza5cW6+2V5ZX2TCYGSqCiK2dnX5/4tGTJ9/7zqeu8BvvOC0dFymdYIJ+8MZlYa/ajBk4HYHDZkCFWYL22DgVucTBVZ52pjV+5/jGbt+6/cXX91nZxfAS/UJel0CBWwQhmC2Q7HFq/YmKwggA6TwcSCmeGHV3RZ1JuiHURccCaBoEDjAreskoKg0ZhgSYrd2DlY1tXms93traOz4hVmO6jfBxY2OTVm5p6coCkZArDdVvZ+CjH2gJdTNXDUlQi4HhRWLDrshg/z9N1EM9iDj9KQe2Xj1UcuFb8uaulIuSK/nQXHKTJ8L3Rz0DtPYjSxR5kjjlYamsYDCqmLw6i0DhzEMhFthxcwWwOUqESgYQsKawkbOggoPdR3E0pObCPLaIHOoh8s6d+kdzSiLzgD4sVWrVpoWTgBNjC5JdvQk0U41+fRI8ZaM1FsgQolFSK//ijn0iTAcmWO9IQWMDtchSwVr4EGRONJ5dIvGliLvX7xHTI1yCGELiTosNv4Tc7To19uDRw4Ovv372cvnly1f4b5wk7xafuBBBlVzZWF/d2CDW7zYmiA7Gum3Ul8jEsWMUD50gZDo/74zxOod8ABWUBC1iTIhLdJKKQIkfkHSNBZp0dr40t8AjhpUQhMKgKjvX9pG5cGLC0V5qyEvJMg8IAcWPJJZ+iTAz7GCLJS+ZLOAkQ8LXYhSJVayA17l/fffer+/fX15dY39wctErAALgMSDX8bK8z3ExFp2Duq6+CIEkukqEXnYzsr8dGGt5CsGojF9ow3CxQ8DyLxIpopEO6+BvdJRrc0FC+Rtd8wulxoNhHOol+dCeI7vK+l6E8EJmMoqJHJAh5OTMv3JwAe2g515wJMkc/0YHZcLrwJOHpZkuGTBP9vcPF8wfOkBGMwtCZB/Bef0b4kp5HovkxbOCW3VLYSOR6jAjwuS/CHpgfISjNu/ippaUy9J0CCrKANlmVs+KPVEQ/jCyjwc0QmbT9S5DpezUe/nqZRqfQo4qg14mGiGYmZ9b+Of/47/Z3N9j0oAv+hnetGtMHjcYaTlj3o1VomcPnjy7ffNWaNbf8zoCm66CNbWzYBNboCEqy7ZZ3wmXGI4CDja2v7fHBJw24OpSZcmADTApSn5mLfZPjhLCSCj7k7lIEJVKTUxy+QJA1ShQAqU05ilSCJ/ggK9zVYwe8VNO8r/iKzgSvdQGp251ZoS3tfMIDNBXRpbAiRXiLAWhSujdPzikaPoJzjmwmj1FWARijxVjsPXWo2Lrkm8tIGxQZEulNBDGSIpikOsqG9Qru5xHhVOkSlSldKCCtSGpgKUKyHbwiac8Byort0Y6XSlHHlWlzSUcG2BKkopVR1ksLcc4J0cwsqj3ZDWVw9/Y1ajGVFo9MIONu0qXguVscg4QV0zUoUQK6FSX61xRHb/FRkgdHeSGkzjs4OeJfzBCOOb3sSeAq/MWsxZ+kIFnCbUYBhabd34sBWimbt64+jd/+zOmms/GkT6ejsX8NhcYtdxoDJhBu3r18ta9+67dJBWVdfhxrGstWJav0bCNJDp58a5mxTYrtgkm4jraPWYSzUjBrq8KB0XAIa7WYyIGvpeZ1ayukGIF3fEhPXhUMaRIHxWDdOYTDBjlI4cPdD/SJgfCGUhObk0gailTSmbZIcc8qJQ/2HqWAJTiIOKiWHruFsNk7eOKLQ0BkxJn57v7e3QPsrOT3YNIQuNB7oHfYBE5bR8mDiZx1aTTQnqMmGLt3gYRMRftcuIiRJRnEFQeljNPzJjM/JTf5CnXoalkMHTkNmCoIcVUFa5gIslV7eVBlU29tS31qWXNY4aqLnAOciWpqp98gjRj+RuVKQ2UaRa37JtHlS6QQLDGqmTAwx6eCFZEvnG8vpejF+WS10oMgRSG+BiH0yZQRN5Amld5wK90+sJJWXQsWLY8pAfLMoeJbh8lcAQpS5LDMaMSxoi++51v814yFaEG2KOjiMMjwNuiurFgc3VtnX0A+EAOQ0gYFRBY5kOkABrOh8WGWNXADBOt2UgQWJRvfrLnUgkr9vcOWM3KFy+P9o6WV1d+/eU9rIuEIRPUvgphj7iF6YG1Fm8P2RUWvDMfUmusxkD7JBcGSLTkgSJIaME5ijaQQEY0Fa5hiLyTQW5xhVu8ik9xwjuIRNmjHGSV1Y0GmzqxQormAi4AlPRUJpz0SQZkYGiZ3QHZYBAcFIPDfrawVFpwKGdulJwq4K8S4ly8YO7MXx6OzlUOSylbz/6leHnmmUO0qucloWQ0jRySkuRSb7JG9cTVB4E4yuQ95Uohyhe45gso6y8YWJLjNWLeVDXlyW+dUrykBabZQ35gaAxBpipVblQnRIkKeYwggMCookRKBp/qgF47th24YqobxkhsFhAfr40VOOoHG7RM9JcWF1Y31hcWlwCOInCm6WCJMxUgazLdvnV9ZmZ6fXuba1YHoYK81M8GYXSj2fqQgx1X+SzItcuXCfKpyulqViqkU4pPtCFhIyw0Xh9PtVFlMCV8bjXW1taIP1jtc+/+fT7OiU2yLyr/MiDJBgITIbkKTe2GyoCoHl1niKOjzsuTdB+6+TIcr0pu8QWQc1a6MiSAWxcNxEPvxyEv410BcMhLtd9djIo2KkWIBsP4EzKQDUNH70lB8/m2J1t4u6mAu/kxoSF3GFsloqMPQAjIbmqMstlS8j06DIadNGxbiUdZWtgO38spogsObyTq5F4fXo/u31CK0WV+JaVKqBTHO+kYlSwXURXdQJI5Jdub8NEcnlu7MPPcm5Lz7ySWRzlfVPRG2ujSiir0qqQA53r0O8r5d34vyklMdYA9fwoojBpRPnqcXzMjQKIB8pRaEjRYFnRiX5iTvTUUwrABd+n7LuQdXLm89MWXX6D0jqA4wJjeNs90pA5+0J++dvXK2sYmwziECag7fg8njVqiWrAQm7r/9PF3v/NJ/3yC1zALU3lqv4Sza9jarCo1NkNDlJNYoUV88Pvrhz/98v6Dg31WwPmxQ6alMS07CR3oBf5FXw3aBi3sA/1m8J+9rednpr/9ybdnJvs3b107Pjpih7GDfT5Z9epvfvX5i7U1JvlAn1bMgSEjGGxAHeFI1dIe2VecjhHAPO2AzMTZ5mRP8BqrCJlp4a65s3f4cnllcrxD5mbPyR34gI1BDYyALzCCjVBnJRsc8SgyHzJAgFsBAjFocP6PHWCFPVZaayaKUPDvHmasUpWz2agFy7dWcXijiKSW/Ektuh6DiX6ZE/SsdKRAqbPA9xzQVXXS4ZFfri30jSPIBGCQ8KmsTZ7kr3Kb9Pp+hHBVZgRdOMEOIFx4kCC2ufW6emyKluK6r+S0NSZFRQo0ipZKfPkW5SISt2F3YIcx09PFxcVf//rXfF/Prbry9Z1GB/+FomsSqAADrJcvXfnrn/3S/jKgXf0GfG0AGjmRtrrKJiy7LNTv9dr4Rr+OY7XiDAzK2Qmhq5BR1CI2nnc6zLmNv1pZ7Yzx6YLkcuM5xrE6zEJw8A6ytucLxs7XOorKIOVsf+pDvn91eentO+9O9PgajhPgoDs9Pcmrlcvr69u8YH/ELnyooi0gZNDxxTeAb2Efqu61iDCP7Soju+soLuMJDtLi8h3pg93s5Iq6s7SDho9wjZfubi4tsg/SWbusYi/OQEugK4EWHhwe42zYGRZjkP68xglAoME8KkVQMiaigrnhYmRdEhUk2qwgk1phya3dEeRa0oGTPAFVwYywA1lfQ4nq7IWU5jfJYKUWJY8/CqmYRWDYzSqpwRI8qocW5ijoJqs5zVR0rwJYQTMDNakrcp275LSq/PeOazNUYPNjfqjz+qKi0QW/FCrZZaWAZZiwC41cqpkgZJoZfGRe73M4hhl06gQJCIVE14fWeINnkq9xvHq5PDU1g9Lq2uoNJhkwDCRCT5Eg/fLlRRw23pXP0HKaZDvdsTHdfN5ZByxRCXvsXbt0CYdLhrEhXQU6DChVwjOMrjWGZrMxXvAKemmXvvXJx3/1tz/jNTrQpSDbUdJYYUsqMa40X7HhXRoXVjOCT0eE7uB7t9/6+L33+CgiNoD1ZiEeYQir3M6mpmev37j167uPaLrgkBESYY3sYNqijcMOLyvGKW0ZxFiBoubahoNghspxFbqSwWmT/WJhl4vqUOjVtbXtvV2GtU5OsXVWrLB1BX0Hhwu2t/dpNztdVh8Nxugns98wHxY9p5vjSBkYAF+H7QtH3hKsMVWIa7GbSnjHAxtAwjXXnJqkOCM/7srBxYVQjROBab6RLnFFkbRmPmL4q/SIYm4XQJK/lFNRUg+va1lX8qTS1Ot9uXjzJxUC3bqRrn8XuYH9jUOLijKWVOGnStPU+KgyiUEntXvpXf64CsHm4IjSqlLasaMu0Xi5JDxISSyazBk0idNJVCIlYadEJhziG69jhBJM7oIDLbquha+5zsw9ff4UD1sG36hV+uyH81RhXZpfYAiVtwe4R8W3znbQQRSF+lSeEPX0+YtPP/4QDQyqQSxdDqRKJWjRzsEBryJwAZEiHtu9eunStz/5+M//6q/pQDOF5RfJj4/RNJSHqIz5um0mt5jcPWI4dUCXeoytp6+xVdPcPGtBmJSg0wx+4ZNtT63RZv9q4YuYXx9BVtBAfIS+VryUK5Xs1Hc78Y7wSAhlQNYN7EmEBY6Z0ny4cx6mNtba2t97sbIx3u1t7O+t72w9efKUDhNb9LHjAJEcjuGd22/R/DlKDTLUJwoc8F//RA78SqmJThLyiRoVQfLcJ/6ki26x+G4BlEM5khoLiTukRLSlgKxypQWyYcEPoAcCjM75I0yrSx7vUsYnJr8BJtfcV3pmLclcmiVLlSTu/VaRJUdFQLK6DTxK2iREa0OpMJO9PA4BwAYxcppX2FyYEoMYNYY8yGF6zCKqLiKpg5OypnI4CBy4Swb4oCAzEcFTYKOChEs45+z6fj488bVJBI1yLy7N/+bzXx8c7vOlpvG2WxUhSuoEAKXQeD4weePq1V998SVNfKfZuIEuXuZF6DkaCraI/tmvfs3yo2fPntOfZrKZ4Ri6rAzIo37Uik4iOkIM8CW+IF2YHCqbz7776bf++qd/SyckT+QIBkjfc2/9kJVIaCYRilsngTsNA4uc2EuC+CnD/YDCEHDZrpQmBwNfC7Oz7Ly3t48DCT+lQf3GgsOmim9FB2BMLtQCnqKXxP3y02SQdrash/myMLtZZ6s81tj94u5XXz166PcRjk9wJgBnypyhYjjM1hWsvgIIlKiBsIEOtCF7aM0INHISepwMeRQYIos0kUR0I9I2JRpP5pJacNU2Rn/kCaKlQFHHAC8JGfsKIYAoWldR/UYx8SnZOV/UNUqxpt8+kqa2V8gGiSoTSW8WSeGQ53OeSFSyWlN1UzJVALwJCUl9A1i5Dy8uIHgn+hUiXltHMgk8/TfFn2tcG44O+LgsDIlmkLaMawhBPaiW7Hw9BK1dXlnp8/2+TpvN3idaXfwcoz3Slde22K5i+eXTd2/fYSH39avXrvltQtezMfo505/61//23/Ea2ObWFnv/tIcdwvBWh/7qGa6xCAHPTS+YV8OolPcWlD62Rqf67JxvMszNzfF9HSYM0UNIYCwW5bdqd/462dnzIygYlTNraCe7tdiLzdpstCe8wwVrYXz1Cu3tdft8y0O21/NKh5GHk2XhtsF6pGibhCqbCan4zy6R6sgNveH22NLcPJs38SLDsxfP6AaBCigRAsHqYtAYJ6P3FKEszoMLv3eFvRo10s6wMwcvRsFuqrJy/BMH1Yo1jpkZEnsKCp9KdVvJNlIGoEqcMvIohUzMn8/M4I1MFovqKJfe6hHtE5bxFHNycMuRy+rEzTcTvH0TJrdm8Me/ERzjEyqvoPFAMkSp/H9Nzig5difBpeJkrHIDpHpQgaeaCvAFRBmROsJDBUqZ/PkEqPlR+Y2gcECmKF68a17lMJeJgyHv6U/0x3GghB+EwegaqayhmJubfvrs+Vu37xBcKkfKc2gt4ocWsXPei0d3v/XuW+99+BFL2XqTk1ZGB7fT+ew7nz58+uQXv/o109W3bt6gojJYQtxLab9MSuW81pvRHWaOKWjVtgzE/yf8Yj/3Hz8hcgubme8aHu8dYBU8DlcEQBjNfAKrUO1JuAuRy35odYDsIiL+M4RJNvQRcMMnRQHKalLbIEeQEFoGVQzQ4gfsEGPOYw22smOpaXu8w/rWA2b2jg5Q35X19RevlnmRDbCoFC1P3Lo88b9SgNFqtsyya8FXnOkzswF9B2nQWhluggL50w5aCFJGPxc6RNmoSOTkSesQtH9efuNA8oAp5qRU+fPgLHSO6qdAsTowtNpkLJWXjNXZJ6V0gRQIpcQoXx5UquoTcIur9bnIjPL9//0Vt4JfqdQCVdr/NhxZB+46jvyjSkxcqkq5kAkimiXYcfgyuln9Q3wXqCn5hDyYAUun206vRTcYoGm32Sb1r3/+SxZIHx/3UQ7CfZY1iyug1IHhpUvzb924Yed1MJyZm6FbyCv6KATKObcw//3v/c5XX919/vzl+XcBT5yCDoASYzG4Rl0deKBx9C4HuzvlA1YolRxUic7Z6w5jw/oASBItAJh3mFZzmg/aGa9Xkd2jhkEuApPJ/iSI0ZcFQ9UMlwciznHZ0k32JlFa6tSW3aFoyOisnWtiNDv+p3t7uzCyNz7OFpm8bsYnP1i78fzVGn6CbyCygIRi8B2cgI2xoNPotYioA0UPw2OkAIW43YwzoBt8N+7lyipBJjVR3P6WSn7RN6Ksf6YpWhms0FRWrhVWORexkUB9o8Os5DdxlORvubF4YAHBN2UVDU1Csr+Z22zcj/4HQGUppaZgKFAgJlvwlOygBlSe4UJdr0OmMOV1BSmX21L8Arko7ChflSs/5ii5qmIALZiM7stTKqJG6ixqLiusGzrBBdWhTIzT3ld4XlXGY7jBAAzBs0kU1P+byDfBOlO+d5VbCQcgq/GODg43Nrcm3TZ4koAeNcMtEvGCCPJGuDMzs9TntFXQwEJABqDsr8dXRd55+86zF8/5AnmXb676Ir/dlcJFSWMMlL5Ho84ro8xAEWNv7dgV3t8/2N7ZfvLsFS5eq6EA740ZUajhpTOMsUA/ODCzNmT/MKqZnurV610aJJtnTImgKuEgNdFCTE1Oyheaw0bz6tLSnRu3PvrwQ0ZnXT94era1vfXTX/7iwaMns1OTfAHn2auXewf74ERIH6OyT9Ns8RoetSq/LEJnFMtYXzrgF1z05DipA0S876/PMeQH5eXl1ctzs9rcOC9tsC83mREPbLSZLn+AAb6ggAlVSGhkG9ARMZH/QiG8BoqCjHIXDycWpCUjKcmdNFIFaYLomof6kpZ6KsCBR3IeB3Z1LVgoewOBPDWjQPizqBLitkLMFGsyj39WGZTIEbblmShxWMoMVXFzhgcmvXGU26R5iVMh2sh66ZAhV5E+Vdkak6NglzpSp4giNd1QUCqgS7jE17jZ14dofgoPCr4YGdk5Jnnhf2L85fOXbICHOM8H7GJtlGI3MAdzEXOLi5vrq6Tz6jsDmC6poCMRRNHM3//dH/7f/u//z+XVdd/pRep8TCMf5NRxyxsUps5mR3/2V3/78OljGhYSNx13OSZ+4LVijIfo2zBBSmQIcQzOmhSuy8FiDFdlO8711g1CmnTDna1Qa9GriI4Ya2Fxbqw5Bk5vXbvy2Scfs5fGRG+Sh/rn8xojUnxO6v7DR6tbW+z2dXRk8IP90Cty9Ek54eLtXnOty8lvNBe/YAaS0g8WVSwEhyHG4BBzdNn6zhVW5w5PhtlAyU+dw2mMANhYhaGQqMD5iz+g/tYhcGv2iFyrG9mDYHgmah52BuilANZWMS1hZKr8xVUtYEbFaROHbit9EQ6HWI2qSUYzpyA/eCIo9f0McopE/sjApQpEIuqgr7RMMWHxNjko5IZrb17Xw32q8IFlZUh1VAVfPw62BgwZA2RWxoCzZK8ygYzCMUOEVZIrltk9MDdtOiyLTxUX2njC9M1tQg1adElWQIrVDyyw2O7ps6effudTwmSUIrhTqkKRsnNzs6vLr5gWoOuIJcD2bIqrcMn/3nvvXL929fmLV/SqtV6OCCULQCKNGtvDsOHF7vrWDu8xM8rEYC79W0iQ2+nTh2MRQDhASOWzYgysRaXjwPTvq9WVvd09hnVBjhaqXfcCx0Al0t0Y0s+d6nXfv3Xj048/mJ+fY6QVEAhMh+xUV5M9iBh9YjU5y4wwpLSwUFFpve5wRDfdCzjEExJQtKL0eQgkkmELpThhjba/PPIzLex00G0NTxtHhye7e4cfHbsNXsZTgcNRGTcgYxAVi/+eH1Xy4lAUI7xUNnt5ah+aBG7iaf8MnzBSLLleHRbVFaQ+MnBY8ptHNPqiCFRJI1pEDeSOFShULzwq3ISUS1PL/2+gbZrPR8UsqXZWxbm9OFK6oOZlOaLZFAZ1E3hcgfcB/73lnwzQ18iiSMTrjCJbHxwvQhQN+c8n6Jkp9oVbAgAC9YohGonbe359/9H2zg7v7Uz1ptB4pnQZm1TUBlp0rCd4y+fg6GBy2k8o4JFt7lUIInG+vjf1D//wD37853+BdmXFRaaM4GGiAHnPjG177NOPP378/DlBBNESXVXwcqEnRMbmNSm6M1aoGZODRa7MBKD/+GteenDja8ZndvZ25hemCVnw5ShB/E1xTTJlqtdbxGwnp3g3lE8gAEhtZRx0jInBITsjM0bGaierILW8QKRHYSGsr0dXovDHpbN0t7RsIaATYMZEQbgZvsc24KxvBdGikIdiT16t7p+ebm7tbGxu0z7/oz/8Q4pIk3KQuIrvlAGiqd84zJjcPvXGY/Rb7qoUEgVnFnEqWblVO0uWPC45BMFVpUlq9BvHqECVKWB5rBOiVJAMly+QTaVWVC4KCpxNMKngEiTeqCaAUiQFxKh6GkjRkgvMAnn0/A0ghboAKKnWmD4jlfsXBMDNAZ8Ysa1BKtBVRtN0t/Q+WcGAXulBEJ9+RQFNz8yg/byOMz9Hf8CQjLJclK4R+s7IJrtOsz5uuDhgdJ7VROzO0pnAI+NYGU8ffPqtT7766quj/QNmJUDBiCWIga4kisTw9p23COPZWYiqmZAlfHD2GEzSkUA1dUBxWozZYANYCD3diakZ8Gz9H/7wD/n2+cOHj9i4C4yJnzAasEwXO82b2tqguZifm2M82JFNIcqamAPDYPBsjN2SGSCSfvvp/OkJ5Bo4h2HhprYI5CJUbAY8+UeFsj/0JEBBtUdtt1Tyf7iyvvlqZQ0eMqjV811Q1Z90inExUsFvaOJIpN/4Fe9K4IFQ6ZeAOHwWBnNGBkHc5NEFRZLPnMlfXVwkv4lAlVV4Id5zXCDkWpHnqtoKaHSYJwWRZErJYJcSPkrmyobKdVHVXHsKhTKugCr8Hz0NibmJjhdT/21UM0cpd8GPAopTmQo74QRYiQdaZfMWnMyd+phVGLYdWVKFkg/rSBQ14G3MDz54jzUX7OBoK4JXiJoCCa3q9aeWCZBOz/K2JxsFMVDh/Nmgjs9u9Hvjv/uD77PH0exwRpSylFWPHVzEkM2OJifpivzqN1+g5YQtjJMyL0WI7gD84BxTpDpyUlp3jZL5HYwB2zgy5NP63mef0Ga1a+ds+QjqhMsZCz7FrKmMKhP/8LpQ6/r1KxgjzQ51O/HQIBEjoI30K4tMz/X7vbX1dR9TiatljZHSINjQOeClrkeEPHYMFK9DnlipWqdowm646qgzUChH82FLwwAevWiSWIfuuqnKnJRDhtJykVMR65s6abIyfZ0n1XBbVfjGsyoT1asDb5b7LYggqXe/gFBQf11FAHkiSyC9rsSEgpA//gU3YQFlhGnKjjC8gPbb1QS+ZYLKG08raD54M9UqUhsigHOBKwLfOAKPRIMCqMxthBBUza10YscpGvps4d0tjpfC2MPQXsQgEQihP5tFnNHPfPbiBctzuoS54+7nxVgqCmenVGD12bm5ew8esiQU8KgNL0CzGHmcTWLUQ0yrduPaNTZBws2zizDAKUQXoHREC4p4rCW+UNy8Sz8BrNGTY77jgedFVoYr+G4IAhgjSI5mJjm7CLNJZbvTnZmpX708//jJS19wjtSoO28UF6+i7qL5V5YcCwMOd/HZLBZvg7GT56y5bbLCZPbh48dwTfYRYdMDcVvhYoKqsi8Ga5Qe9BCiwQabHmWfbbNzqPClr6Hdir5uSQFqFP5CVTmAxOF1BS7QI+sUEZn8F/EcgVPl8ifp1bMKaHWXTOXxqLDZZVEpCEulxhQr8QGVvlm6yufjoKgKJZf3BX4KlsskycA8SolANWFU3op+m4S/U2XAVTD5AZx4cshZ/1L9CMwI56BkPakh8QaX8bsmhs8KnzESBIUIQr3ML3xAB+iz8n0aPIQhbrPOnOnyq+X1zS32k2aIgx0c2D94ZnIWFOgTs5AMlBiwwSWCEt/exNsxkjnd75HZaarsiIoK0AlHD9jwgvFWjK3bdWESg4xBw7YbEsAT3SLH/iFz03uG/iyMY0VDbQxP7VgRGulnQOz6MppEcAOn8cTwxDYB7Kni8uVbe7tYqQsZmBcWS42Oud7wDX1s1nhtCI3XQPXX8ta67VDw7gWwzmenpml04DGPHYG0lCE+6k/7SO1SpvFGcPDP9Xx0bHytmU+DyDsyYbiovhZQMd/8qr7FHTXj3QauAor0iJmzoqZEMDM1B0Uvnit8YFOQRymYX4We/yk0Si/FzQBp/Fhq9Ay0AlQczCBD1RpYxfBDGQoLOtKAgMwvDP6bsaLKlIsjILlLFYFeHhMamJonARKtKykXhQFbKnijeFVqlEfkC8TgXl2HpeF5eXUxhXjGX+gNPFAIBwqoYhUIFNrisMKEmD+qgPKtbWzT4URJnjx7jrahFbxFSTsA6TQU9ASev1i+c/M2fp2KgMZIqfIADF3KRuPy0tKzZ88W52cbjTaDSGwJR5e37bdwrJnM/X73i8/v5nNWeUkNCRPhiAWEaAqigbISkLjU7Zw9gdV+WKZe+Q6MhBji8cqnWxRzU3bP0jRYb9Gfal+5fmN/ZzshTCW9eAZZGPpx0iooRsLrQdLgfgK8PSRUm4x6nR3edTmFMgM4ESDmw+rZFAqzYFEdxgdjE/7BcMo6RS8E1YbSSl5UR24GJ4Epm5PuBPZ2ehYTI0fJpcxKZmqz523tnPIjhzPApfmRi+p4aF0u2ksWCfF1p8CLRCyd4kJOi0UhcCZ/qcsKrCt8iekWI0cMCJ2JRUctig1WOiRqPIW4VAqVcFJUAlCLr2oWstc6lFRIwVQHSskmzhSkRJTVZ4AVfzSAs+kxDCoSkmhbRqBJjwYX5AIF/4JvzUC20xkWK/mrmoVcisckVLS8ks85mJhf0egQXAaMiH/5+RdZ79maHO/yDQTyMWriduv4u5OTh48f/cGPfkR0Sw+ZlLAF7ylKIHn1ypUvv/qat9tbffSbDsOYoVnleRX0zOwMXNze3JyamQQvNWaQiQJUkiOfWguOfGODpRYyDflCFpi7gA10vHbQkYeFcPZNev+dt2kiWKgDvTVmuY/cZp6gRQzJTroilIOCwhIMzx14Fy5oULVeP+EmQmd5hbcUYZV5v08TwRd5WSXBppkYHBueff3o/v3HT8lD7x44qdaVW2pK5FYECQGg6AsPGQbmYbBiSAzmM+yAhjI65txNWWIu9nCF3A77wihFV2lALqiISiJmFCpKRp4c1CRxoblKkjoRCUo2jILzIMUmJbrKrU0BCLkkvBo/H8zMTNF6ybkUhmkVKsgTbDXmGEcyCFALq3RazM3PUV1ctGCpefQQQoODaBT4/MKjrE3Io4gsj3kOtxWiwb5khC7hc1iObPTDyl6GUGfUEwJDMQXJYS3JTP4YpEy2bVbJeRwTgQXMwA5rs7NzrO2kx4g7oIUkkkE7mWeAdl4co+D6BvO/u52ZaUDqwm0MgpZuZ+jGFq3mc3Z8uf0Ws1uE63R8icBZsiFijNe3xm6//c79B1+32o3aBEsi6JCgHb6hDz54WPbQkihHpajNZ9Aei3B9HUDQHAIbMlCrdkimVp3VcEzjqV3oEIOtzET4Ep3bfDMRaMwTJMmL5/BdO+ByyC4dgxNPehN5x8Gk+vzs5CThHW/8fPjeu+y8x9Qi1dPqgeL+/s7YePvBk+eM2GK8KgHiE0eew41ICzCKPXNM8l8zD7rmVA4exJ8lWEIORa2jQJRE2OYSJU7A4cS1NyVF5x7BVjiXZOgp6kVhag80ipSjUoZgJvsoroKAGhcUyGS803DUZ0lH4K2YaouVFPy5D6SCn0DMgj+BmwL0tthA0Pb+4iCloA23AKOFFACpBaGGObCIpwFK9kDkJ3TbLw5u+ily+FSCTCUASEUqwYhjbzCxqqg8MqN1Qan9VSBxFM54TXWzfOhmdpZAgI1H+WPEBhGepdknbqckO7izLnVuahLmqEqoHTwvWHmuMf7z1b37t2/d4tUsRntgLHCatA1yU0+0sDT/4EF9e2MLgGyitHt4tMHnGDY2V9c3Wdj07PkLTE6WYpzpFSsRTQ5iExQgOOrL1hNp1ljYdv5Xf/tTdyouwkMloZFFG436pFpOUM6rZ8Qtunm1MxEFmkmfWwUFaYwweqx4CMz6vcn52dnFmanPvvXx1OQ0i8xhgq0EER6uuNWf4z0HWY8XpTZA8r/SDH5tbOiLgbOiIgeWSLvKO29UR5KaZZ9HnLDeuGJEIokeoGhjl7LEF3prwUCdf1UmH3tp5RRJajmTRAVJHj3MA4yugLAU10JSYJTOfxWTf1Eu8FLzBBIqKhJTFby1ZPRQUF7wvCiBakWJEjIJvwAHlOwxX4p4Y0aeWg13nPjJlY+kulQaaKTb2wNriyQrRcQ7J20g6yALNuJeSA4BwPNW2AXxAkWulkejzNJaECRzvz+JuI5OjtnJKkpiLsch03pq+CxoePr09o1rvLmJ23bo8HzA+jWeuFphyNLRqR//5V/+3g+/P9OfQKL4ZaJy5I4DRHVwWUztX7l29ec/+9n9p89WN7d5nQ3vTTuDGWB4hvtYl84UrWELGsmW0RmARKNY1Y9zhagiTQZy0EaWSyVEJh/tAtW2WkfHezQf7NsH74jxLV+ehtHsZNqZYB0g7AV0mnzZCjAetyY6EzcuXZqdmmAXR7bGxwbojTBFQs8dTvElHb4TxfAWrw5ZO0mqEHn4J7/p5dt/iAbDP5ps/IquFySUheqmCYUI5gY1XBfqeJCZHPAxZqLGcFjQVInmmmzxATzlzkfV4RNCc5k2sh+vhJszDJWdwqeofxYAm6oCM2reeiyDParyiQRq9kKxupAsl0NhgJhHRDRgs5vVI6VLjakr2DLuoKlripUZkDPan+pSMLXLBVECZqlUcBKYurjkkXFatV4TIOIgNSMEDKU8uBcjnnjkXknDkNyaZdQQmRfmZx2ab587in/Oin6GD3kNN+/lOmEv+3jzZndnp9WcIbZmzF+4blehkAAy0e/x7al7jx5++sH7BFrEIGgOgX2jY8cU0kD+0uVLK5tbv/ryKyayxjvjrD81ZCZ6d8cAw7aIo9bJgmrII6WwVtOzhWCfDRQGQfCH++Uzl74wGSHDQvqj5+evVlaYQWPjmazF9mWdKKzREXEOVRC04emxO0UdftF/gC80IKy35eWj48NdgjksE3RIB6YUGkqdYwbs4THYNLyx1mgVXS0sHnyIt2gNKQRKEb2oKotKGpVCU5B2gRYwmVA77Vtl8pyhvXhY0A71lbkKhOcVMMWb/ApPU9cIVJei5CVfkb2s4t4GULhkA0YqVdW0SyVYFMKc5q2wFx/4GtAAV9TyzMo4l3SKjKq2g1GAB4zpQq4w9xqAcfkCyC0J4CW0ZKvKSTeZxRflBybm43AJVZrTy/Phwe7u5PRkCLaekFGV99YaYjlcYjM+F/PkCPxRhbrQsEWjY+lRZ9xXJO0HEjvAFgIKBcdRTkQ5breyu8dnn1i8zeAlYNEW0MtaY/f0ZbT0F7/6zQdv32HIUQtBla1Z9vJLPSz9/IPf//3Hz1/S2x+fGGfTI+ycPVlQOIZkOBg7wn6IYlRBVN2XW7i0LIugiPMByt4wvEc/qGWFN4uQyEcOsOQZOs18+K0b13mnP6MbDgrxWEplBSZ+yiCAfreEquGO5eN7iPdnZqee721ZBKSjQ/xY2Lc37BAsLSw8efaMATATSQY+UZHSZGCBJYrBgxLGP/wACeXWD1E7lSIdiIEf/nlwhkFJkxIVS8lFOZIBBmjMuS5IC7Y84kK1rm4C1MyCG1WuNkGB9sSD4EnpNKwUi+kEOfKQTEVcFJ2H8bphq7YWSfHS2qzUw0tKCNnGgy0JyU/lAjF7ubABJgPisxNo1hwFbIBUNfJIww63eCrs5E+lXlJhatZue5N97hjHTkVCpQoYaDYxdWBnVJynHty+WXWeJsW6CnGsr+7iB7EEg3jA0VOI0QMNMhTQcMCOQ+w+ND051fTbU7y2frCytv5ieXlvj0XUu2yuzqtvL16+ZKMkl+K3XfqF5uIk4SfSlM/1JjsQv3XzBntFElEgF3SXwSL2iADHZrvZzmgYswj4fv7sibJmI3sigRFdYVSOtyKZgAZV7AFW+X4C2Mnr89rszPz07NyjR49mpntj7SkbJpfBVX4La2PJtySlkeNcRmcrBkXeuPwShKE8OB6MEthRZRdxYLmT3a6qRwNte63tYYD2rIKxCkdsJ6kqt6ofAajdtKSQZ4gEtqKkfqZSxJPmDxqK5nHmkU8dDIiAlaS9EACUPEnwZF1AyJWVoggqPBf8C0DT9CjB1ucSUEqC9qg5EpDFwC9tsbeqtfAqWPbvPazSF391KNwCPDagE6UMXtOi1kBOwJEn1VEkkXSBQGYxkcAU4hSMY63mLxMdpSj3IEdi9JJLbCEFimXwQKRiBMX1pMIko+LkDAB+in1yC5HpgAqIgsCh4iHjM25CxRsCemmfQGJGwAmNypKkVgN9Xd5Y50uAfKZzeWX5+YvnzKb5brHvFBxrhbymM2RG4tmta9eBQ638K6Oi8i3mRApfSMASKFM7HNIM0bDwXiiKjd7ySgBnUqg9K0fcg4u2Aq9rUnBLjzcbRLKNBAtApG3ECIai+pOTd7/6zdu3r9P1obPSais8ZKZK2fT4KoLiz8IkOj3WhzbLKUfTeD8IThIdKiMdjPCLJGEJsnHOQSaZ3e7vGYvztBC4BhMBZVCJpfF9FMBVnXW4nTZSAahc2BAvKAFwpGOKUbWIPKtx8QheB+mhrvu8kj6kmFmSonyUDwmqVcmTXx6ajzOYg7DZLUBdZuM+9eKGDTKFVmwgXw2zm5QCArS2lKryARLmiI1PMH/hIWOYwWVFZrAyT8HJh6k1KZLMhfnBSDoDw8oEA+9EtGoFhQnTcAyy3iqqI+SYUUChqghX1megxiqoNyTzvCRadcZeBI+z4AHQQSDjjQgRr8cdDg6GYCBwD9myfQuvrFCABXZ8Ru3Rk6e8LIkD5O2FSd51dt+7E1b4iAUiHAy/uvvgR9/7ASJmhCmeDjypyH+JF2pzs3PkRaF5Y2x8anxrh5nsIyqEGVLuqgUXXBB0eOv6VBejcgm4E7sciNWX17p9X2suu5ODt0oAm/j88W9OzlmhnWVS+vHR+I8mD8St7T0mmuGOcol05QuHL/TwrZQuIdnB/sHs7DRNI8kKD8jpDHDFGw7ME1MZ2j/d6xEsLS0szs7OMvRMxp3dHV4yWtmgidwgi/ofuVKZoJAHxDlApNiVfWr20qPIEiTjbk24QA1c1QDZ6E9UTrQtb5q9KC6zShgNCH0UqCBQTk+AtkWJuI084C42kIBYzlAv6SSRDaUOVF2nRkw/jfauogK4edco1otkqM0FJdq+TTnZI3NjGPwouVGtyN5kcRJtAJetbkTGlDQvIRqzpI0FJpgEZXXRtv2irSlsK2qtDaSHDYHqCav2wTU5wj7QozsaAgVn9bCKc2By6Z2UhRxfyWo2s4qu5TdSWanPe8zzc35n6pQPB2Ad5+O9CXjLwEx3nEF2sjd2d/ZYmlSGcdAuagGVl8uvCJDoNrScvCYF/hD3y0fqJO7pT/J58j4rkWr1fZZkUz/9BzqQ+FdmkAsHwBOiIIuksyO+OA6aLl8DMTYSu3ntGqNY8/MzrBtqFaciIdIzmJthA4Jx5seZLu01WeEd+clthnKOcRjMnDPn4Nd5M8oDUB4xhIp1UB9vqfK5dhw2iaqGK0b0+REcEgc+7zn0UfKbV69979vfvrTIe6oLjBHt7Gyy3Aru7u8dPnr2/E9/8lfMvukKgnskDVGxRccu+AiQa7YVSgTANSxeX98CNSYmXWfOKN7wnIXkBII4IZg3PTW9trYOVqy2mpjs0xZTI59qhLGOUQ0H+d4Rm2ae8V7qRK+/s7GN/KbnZ6CWGSKQZ0wMYBmq85PSfD0SJjP/f3LsjCP4segFsEwGsUwA3BE+PSt2T6MTScTMMML4xMTe/h7+llHz5CTmQxWYdjwkP8tpAMQ8Og06soEV0MK01OERuwEdkMKYHMPcFEAz0DaYTOzLtg57+e41XzSDdFZrItOJ/gSf12M4rj3hflZwg1eieIOFVS2UwjkiV5BjoxF0Ynd7Bzi8XWAjzYjd+dnk1DRrk8lJjayEg73qvkpPGmdtm60d4Lk3eg6ea0ao9czUFBPJfECe9w1QYfbbevb0KW4dhWAsx/cO0TBCdF00b9kz9ctWvrxcps8DCKTBK8SEFj19/vzGlStGIK7E5EODDQZ9qIWMGATxkiIgBHcjbvaTJyLCY8X1gGw0076ymumaN7QUHWdN0eLi/Mfvv/fpx5/yogEdgRDllw9tcqRRf+coGJsi7ezvbm+to/xYuK/JMfF9hkmzhENWsbk9HGARCJraSvwDLNHD9zSatHUonwzj3v/O0rq8AF6x52SnPdWfmFuY++T9D69fvYzZMM6Ebk9NTbOSlgJsZ4l7Y8b+xcqKpS8OngUELKVeURZnKBYsagpfL11aUCLKhsnO6Yxp1pm2JI/UMpl/7Qq/eG1YTt+uNDh5Khw4MNF1X8rArs/OzwJLpasHmkzASIBGbc4MttuzVIUcuhM6xWjCkO98cZHa6vVJBOYeuoxXkJOQFexQPjAG7PTMpG22TZDeXR46KlK6rSQ3+aR2aGR4pDs7N41EycDqncKSzrjGT/uOu5mcJGd4QU/MZQi84a7gIBnV5JGLQxEB2/tkgxMwBBp6A6ZYyOz8DHlQZBYHyTs7Ki2GJqECq5a9QAwq/ALE60KvxIVwHaoHaom/oCbYyDK2kxqLmn0tscVaA/b85EuTfkubGgb7+y5oAAdaC8pmAQSicaQVUoCKoJ4+fb733ocMxDOthMug3dAAoweoAS6DFByKqANTTfASXxJsbSZlTr8HWIM47GRQw8PSknzw7h22VGLuAmWQpUxTqDkhFEC0py6UHQ42tzf7E82N9Zfocb83jU9fX1/e3NzgczjsSsSqpgXsjM39nPVIu6FTgLOGQ9Mz0wxAwWiu+W/TpLMw8mSduaO/U1Oz/enb12/CHNTXejVWtv6FSvP3sYaJcSFIGmA80H+AJMiQkbh5Eq21CrgTCQDLOinIH0zLnKD36hCsTZdVbGJjYgincl2eRx0IXQrmaqxWUVhM5QgzddpEA0TcEwupo14gotRNAVxQijFoD3zgBFs0DBeWAWh0DR21AERjGGKloMQ8r7nIMokSATmhHSF+dFtmAJxdoYbsRWIWJiD54QAAzJRAnBQL13hmXtCTGCkVPkoh5r4Xpkk7bhLceQaG4KSd5MOqMoomE8ggQEkQiNOROrGiKh8mF79A4cU1vhZoiyBKvr6O53clv8sT0cyjvR0WM+CqCb/VeZTU/7AC/eGdBHEDXDAY8kme7a1t2s8OozN2Q/hkvU0AjhAC+X6f/JSK0KgxUi7MUXXyf8jiTl+bwfDBB9rZd3Rzc3t1fePa9dtkMXbNXxlEk0fAptXG/vhe4vLyM149YrXe7hFcHt/e2yZ85/Pj23uHfHCX0WBaNIpH9Z3ucINGvJqdFVYL2twQQiASVIZWAtaCB3KlShhEBlqeRAW2kGKMyEMnBDoY3GheXrx879FT2zpoUw9ClRpAXr6bQm8s3y9EJSOHyI/SEsvBBfBCoYNUalt0V2jlf7mwLEVUOHRCDKnJ2qoHMIVLbvgH02ON3gs5TPeJapc85BbPFBGQXAVkEU0stsC3MKpmK64paE2U1AxAw5g8r78WJAJf6GJiUpARRf6AHNUHTp6QBCyqVVMY8nZY1gT+FwBUF+cdMs2D8wvFghermKa8wUGEgeFF6rWsfgoZSBFZo0U0SvRtip6BBX6F7x8TyGEBqBOhFxZki+fgDy+yswGMX5oCJcIkQk2/OsmoiYZXkIIQ+abqDoZ7B4db29uY07DG9r3DI5aP8l2ytY3ldb/PxHpv9hHVCecALFGAyoLDDEdksuNCDK5IHJViboMB3z47/slf/+zddz+YGB8HTYZtcNMOesi5UIVmk7S4uPTl3bv7x6c4/988XTEudpSaCmCbvdWdvX0U0Z60PoHijMFXqzbIRT+enGDMni/YPVOD4EO2hBmgxMtHNOUYmOConIaFRLuGjv0OTo7o6wywRqyEYST4wiFBMl/uoy38c82F9KsfitFs3Pq/3PrQO7NEbVI+BRAoSaq/yOcnbOI+tYiPyUW/VW30FD7yXB2pSObeS2uXeT7kqdUnZ1Ae1g4OjgmLSYWB1id2KqDgbeWsMckVAbFGHnqocD60FL+WtKyEcKLpBk/lUj0nrzdK0wKGxQaRFjdhhF5uhENWqArbZKyKTi7gF+dhjYZJAKQa6yxAkGMUpkCNHaMHZHXyAAGeEx0hOxSJ9ydhNA0pMQyQ6T+j9Qx6ko3wGmGjTgyZYzPQZUCvlHmHxtlY8IA2Zh5era0cnR6wuGhtfZMtdAlQD/cPN3Z2zG1UWRQPZGhXhSPLpIuzVxGNHNDxeJiTguwb9PX9B/RSGVsywjTKdb2e7xaH45wbS0uX6IuxzNxBLqeWmZOzPkSZ6YUhnWbUkG5iZxxsGaihffCg2YITvi03xipcutfWgTy0OcvLZvL3ev0Xz18cHhzRcmpO6ghMpE7YSNeVyTv2CDvyG6Mj7oA+2RQvf9DBF6NZbSF9ystHkbdSG9GPPgAuUTKMSaOvsAuLBKPIo35eAsojxhUdjVAqcIV/4AgvefFbRhXd94LS6Jvqon1xGBeRAihpTgeAaq2E4A++KYwsyhCOR5DxgtsAABbPzK39UFbEVVKzhAjDEqopGZWyV8KlgkAhm9Rp8aFE8EAwD0dUXIXnMZzHzUGZGayOsYfUZUXJXHFVFQke4R1FJIoUS0qV1SkINJtHhI5sAYcl2Lli1ze6DKo5D1BJwjFWRoAGn8PIkDmlHUMac+v4XXrq1osSO9H0888/R3y4cUyN7hBvgx2zDUync6wj94OuSBmoEi4mBSNNIjA4gRtEvnY6eaSxs/z7u9/6pDlBiG4Y2dKPkEx7hSiV6GB+dobBUPZrgTYMBUAYcVTKQT6qwrJx5HCYRMI94yL5UGO3YVBGv2kaj9jw1Ak/Jw2gCp7BCOjESNgVb40+x8amsVHbOI82F4yLduEU1tZeLS+vQJ024o5MkKmphNQIhHVUbnuPT9Q/CT1MQB+KvOMWNZ7CEShUifgf52ZBFUxmWUTUfBj4XsES+pK0O6M8lgYG45ykoOM6QbSZmwvIMiBqF1RGKPkeIwDLMUoEE4uWxFGlghd54wudvbCB51mi8pcSluaiYGuVIbk8N68WmcMqoETemqdKLFpOrmII+vuCTAEIaM24FLC0gOGvjEpd1uBVIUYqjPKoSA3PQfeWkIGxnN2dUzq6aCEZ8I/sfuUYmrZqJw7gjLAxJOSShyGfEDjFvYkyvtLBDIrQ6WcpEYrB6jVniFEtOg4ooRMIE130EIcriywEvGBqQxnJZH5Gr2ksl8Da52FcxP/k2dPllVety5fpEeChnMqAMqhBwnKN4Z1ud2Z6+slLdsugc1ZEgn8iApOzWC5tlnjLGybRztgJn/qAAXHwDIwZrdvd3iTiR+1hCozAmTpeYptSZw6B6PDpi+eMG43zcv6Qt5PO2A1gk33L9g93dre/+OKLnf3jA1IZKKSoYrQujnJJbQDHQhBnrEj3qQjBPjLiTHW55kK60iyQkoNcqgsU8JQblYI6yjMTOFQATLCkCgQo8sqRJB7RfMtV1cZ6df4i6SM9sywNf8L7ICYaZABVSSLDhRsjJ5TxNABSucU8LrJRJPWlrA6iPOc3FIiKICq8UxDVKCZuFmqETLPlEJz6Xd2ow2DhHUjwR+DKbehXZQPPukijGjNKYCjJtdCUhOsVehO9paWlbp/PJrxC0KxCwidDGkxRWgTkZFafBjvHe2BIEoED/Ub2x6JvjXvFY1K1fpOgwuEyX06gBHjggsnOHUEBw70gZ9gRxUXEIBYiaJdcyx0N0UoABduFEcsImTW+8ff4+dNFRsnP2II7aGlS6AotgkM3BPT1pUsLg89dKRikVRfqAg8RGg43d3YIkE5O+5Sza+GkAXvDuHAVphEizsxMrq685KVVplVo4ViXyCO8BFjCrevXrrGL092H92dmxoebzeXV1fsPn24yuk+XiplyaohxSoBDIrbdFBd7WxU3LWZhLQ7CeiNsVUDd0iBLNugpPPEBIBBgUfbwXUCaCk8kjGtSuOGWJwVWuCbnyhMyB2alTGSzVGF7+IJgLzJwUcAhcDXQG85gQVbBh4upW33ysQCpyiEHwlW9DwcXljRGF1+uo7tBMmnxU9phNKF6rrVxma6NSPrMw2uBaDKFKMCat+S3IhdIyxawKsZr3T5IYS4s77hwaghMrkKrxplBdIanJ7osNeUzgUhcGclDetWjCWeRtiiPGD5xaFUY6ilu39pUNaIlR5wcInZ+kF3AGgNGZBkt4ns22UKOAs6GORashQAVOzR4SY2MIGNSTJiIKepEx5Xxg4GuEPsAZUgkqLr34PG3P/6YWQH6csQe6q4aAsXZcRI85mfmsUxQVGwqDRnkeLhSZ5qGd7SX5uYYMI6wsHAlx9ImzhgVbQLsZrPV6ZlZQj3HubItK3aGjjCn8r3vfuef/Yv/4d/++V9tbO9iU3EDdkVsB9ncBj5pDsWCi+BtUEBHdgdhuMw1ObThLFUq0iVL5CQwpZ8zV2kDuAMaPJSSPPQJOPvAy4uzpJNqbQWuRpIyo3tuOFKAJ4g1oOCV/CJFVPlRjuJApeSVFisb1ZQ7T/6RHCSSWNUrxQnfU5sYwGoqK3lCAyfBOvOu9lMzIsBrmlmtVxPUlTBGcPyLpZIWnCgndtRjU0b+ICOSHsG5KouuVA2PhoJ6YRpWLa8CN1xi8zk6xzt7e0yYggDaqSlYINAJuYmfUHI1jj9ZpYNLBpTO6bZCoPaI73fRZ0GDMlQD+eCFznjt/EybwIQWQAsSDbTIkIFQiqc8sJVhqcX4OHmOT7EE8QlldYJw4puJ9hmD+y4WyFAmz9jekE9QGX/zwg0DTPt8C9HmqQDXk0iMHmLITPi7t264nsJvOmjSlMJ4TMkyrPF2l5W3DJO5mErxmAEpinytxi56ExP9B0+ewCEnXorHTS7seGR14V3YTK0AkXhZjs3VXBIbfEiHn5mh158pF07UU8kTnKnaG8wGJvE42dAPxgn44yADR9gofdwXTpnG/+o5qSaLlQRZTfEOJFW8jeKZLSIrkNWSCmgQzmPAACsKBMYZbi5VgTqYospF3XVHxt/iEO2z8hEOYgC2IXgUdImkYCVWvawQLVWBJ+yUUGMZK8R28ksFiNUUKLGU1cnYigafq7hgbc4gTx4AeuY3BTmDDCGwr6Dg8lpjdJULCnJAUupYAbTBKM52FiTUyMhx96Cl8+azIGyR1MBpAmNsutNmqJIlenheYyI+Wq7PBKAg0TrGabgCANJlTBaIDkw69cmslBgSZvtCiwE6r0KApI8Bx+oeNhXmEw0YDC+JMuUOzSoZyhGW8SJBhzXivASk/sBt0aJi2gy6CU4ZHjC9z/T26Qlb+KURzFtFEufbM5h4rz+5/OIlQSIjCIntIB7oVASXh73u+KVLi3cfPmSuH0SpOg0ZTQ9rM8L+yCdiwIIVHdwbZiU5aGDcWIKAKKlgI4rgipWYWP4UkWU5k6icHbXxh6PcpopSo2fScTWFx9x6JLP5RzeCMhVEZFoBpKsmg/UmJ6J2cMfCUb2kcmMBWzx0oMABFlpb1ZP8IYtpoKJwNugFB7QGHwlMaje/mXkSAv3hQqmnOS2AtE9UoSBJVu8uqJAGMdY3cFHhBVIchbHmT11WhfRQICpJC1NwE1Nr5leURJUivBbwez/4Ph0EdkT/i7/5GWutQYlHTnVyQv8venfQAnaMTbBRV7EJ9mWZyDS/4zR0iE8OD9lml4jIIFybd2yKyVxcLpaD22XwEa7IfGItshBTheIhvcxzhvJ9pEDZOebS4iW2Z+2j3OwDOTj76S9+/oLB1LW1OzffolXJ7pNyxyk+HbTyJdSb4G3UtY0NFmsgkdiAX1qActSaGjZrvDp9RF3wgHNnnC3N5ApN28nZIQSzcOXxw0es4p7o9+OfZC+gEAz8YLiIb0b95G9+mls+FxXdYotIWS9naVE5F7wiAPSGzggjV1okaEAzZ/hPpbn0Rf8iQn89ZH5klWxWAWR474mz1Ui2N8oGKBEoyQUNslNZJcWgwgnyGcKAIUJOjzFVga0YBq4VWL0VjtRdyKmXc+orlXr2HhyCU1KRAtqm1IcOcItDecqXeAEIevoGsgoKV0oGwSQX1ZqFIjpYilVnAYRyf/lfqi2ACxc5lzzi7pFsVlEKxleaQzClDaQeO68AQybIFYLpFZwT+fzv//gfHbGAn6HB8Yl/+a//J57zJ8QYkh1SPnHTZHsUIhd8KwNsdvtY3MU6HbqgjDJBFGQ6zs5WoyxTarPOigXXLCHFR8AGNI2WhLYEVBwJRkwM+qsDdnXUEZDjhhfrWdRz++aN9955b5aXrKf7CJpNh9hfYro7/i//5N89efzse9/5Lt48K7iFbXRFG+FPo0nYtDi/gM/2AWLR/AaTLPBC05k+5Mu7Jydb27t8Ky5jALXO0N04yBlllkEMIACKLyjyHQSCecpFBqoL/EBnLi0uMn1GACYrVR2qojzPIQO9RNt0lqgCy2q5xuVAQ1TQOIHVIwpFijGbOLaIiduRuF7fc+VN6qgeR9CkUXc0yssc3vFfLD38KXnya3haKs2zYgCUMFFVCj4FEGeokTRg2QIEcorJqeBh9spgxM6K47UlHy5ayuLC5gAbKeFGzgRvYgP9NNUHos+kNMD8/eZRajBNVggqQJLJqkxKcX6/WTIJwQd3KU3UiLNCPGhLARSHXTwUwz7D/iRvIY99/7PP/uanP3v+6pVrRGQTRClFPAmYO300ZHrKmSWKU2mjTZvBgis3O2KQxQWsjh/aHKEzlCTEQBdxoLgktn0v6EI1wYiRPHaigGx5yE3wcvPmtc8++dbbd+4wYjvZ61ILAQsmenZ+8tEHHzx49JTdA/jMAsGO8wn2KholSsEK+XqaKxzZg2nCT4USDdX4JNQH773HNjAL07N7ezss5f7iy7vs1Ur7hUisGcHaRhmsaRK8lDzWYs3t4cEhIRpAaDMdBYN42E9OZpG7ncX5uZ2nz4uywV6lna4SIqHHwx02LdMoLiNoi4p8VAjYwBk+kq1oVzlHUUQnaiUML8Llb6qptfn/9WFOjpKA1slfjbLK4SPV03pypN6CgGJUH8THzodlkieLTUAekihmizgKhMggL8pm4CkYRJPNeqUh0AIJ+NyDQC5gh2rE4J5uy0BB+GJmZszTfMFMtL55BAxJYDP6H4MoGMYYvlng4s5sGVgRFwpjgyVMIOyxmUK7S53kKlmGZ9OTvbfv3H728iW5IQfyOaA8cwOsu+EFN0I+ixNIM956vMuyPDfUh7AiOvQbnlIRRKL95CywDQTAx9VEek2qBoGiMGGCfGapNoguLi3ivln3IcrOjxnkU7jVrn/n2x/cf/RwdX19erJvI8NybpZL4e1YIBu1kaVsE4+dXr00f4k32SZnfvTD7zPNxsI4PlTCqlTWpa6u7qDl/GNVMBiqALQ6jLCJKyMAbRZObWwsL+wfIBfXY5Es86IrmGZ9eO3SIq+iFv7A5YQ3tn3yQWrkt02fLzmrhfJac4dgVUfxJ5hGByiShWIKy4rISxbLm2Lh6pA0H1wkjB6MnvOoQLZ3hYsr0qWYKJkp/hi4VQVBtNQIZYIVgzhy5ox4iSRajQ6kSGrhkgIlnYGvQA1vsoRCK4JJmFwIlO6UkhXaWO4g34UvlqXWwPMGSgM4DKv44E/KjDhRgStAR6DlUeyxehpKKCfhVRI0OK9qiVg1P/pXozV5DHrSTpvGDzLC5vHKLL+/eXP44z8vQ5+OfHPQvDv4MeA7gsQauH1Ej/OFANsGF03wOdpqMwdcfyiT4VgFq3A67XEQ29/fsxOc3lhaJxoQZq4KtmR2IyS2dHz5ctn+tB7DMUb5hUllZQNz6exCxIrgx8/4SO5bNCB8Lxr9A3Nq1LA0sUFtbro/1ZtcmJnl2z79bh+aWCjP1EenN9E8Hbty5fI+02uUJHwhfGI+gfEyVjeUbpOQBjNz0y9ePtrf2+lOdJhv5g1rlChy4RdnT4C0wMsczORSOyuU4DB1RzHih+0PyfcIiSeYgNpdNINwy1uFQJ6i/UXgpZDF4ihSXuFVf5EjJw91xKL55VQOKxUlIISztmFwEnCgDWHRNSm0ZqrHPdvcASkHFVEQVWDj8owHqKcklrbFTPo7DpIhIWpPXWpGypNDuDBWsZoBOnxCMVgNaFErUNTdSutTjMxm1WMkyKSKoJnyKGtwVFlM9dfMnqoMSRJdVd3DhJLPC3GG4aCaWkiQKyUjjwJTjlLC3CDPslPGIVmKz3pOanWyi44W24/yGk+7wyqMBOgsssXfE/C46jPIOH8JkzAZZwZcwOPh9IIMYaXPCQqAwqI20qio4iDFBTQoisKziO104/SUTWWuXr6MilILLzlT3n/Ii/mFFuNLLfYtFg26odAAFfwnA2cqozpeM7i0uISh8ImHxSuXiZIkzoiXFVN11g6hxAxqWQG1unSPIO2c0AybElptwD6qvIGxsb7WZ/X8YNDvs0RCA0hINWC9CSvgLy/Ob27vOWOddjNBp/YACnQQihOS3zImuEFEKPepyJAo7YZcYT5SUAdJVdwRkteyz5KVWHOjlsTUTM2DkotbAQO5NFDcuJyEIIRs0Vc5yT8R4Z8KDNWCCP9yawaDQCgpoFWhchm8IJDianYOcQl6pnvjgXBJs1L+xU/hDrzXDEyGUyGVypyUTQWcxE1nhnYAikrNLkwzyxgfc8UZnUl6eUxEgUMLBslFgfRDRC1GqVjhgNepHwKjmhYXH2GKklUCx77EGS+KMADD1lxIFafucARL8Hmwt3/OYiTGA5kqRQujAGID/Ead1cq+7RRUuQKYnjAElQX5kM4gFW/ls1jD8RUoCscjFkkrLSsMfvjo6WeffooxhRhplyVUw7Z8h7ysdcpXnze2tthaXqcCGhIQRMxap5o2W9rt7Gw1G+wV70yhxZ2EZoaL9+56vO6wtbVbDEm3ngEfoz4B2YprzO32+vrK+ETr2G+jtfmQKHEVbSK4s5s3o2N8hY5GTbys3d2/qFoXmyE3+Clc8ZG/EQBJjqiwZBXH0BlzCknKFJ8C8JL7HP4iOAoquGIzPpZZksq1wsPRk6EQ79BEihc4yoX6PUkUf4FDqmEo7bb1mFyOVM8lhmmaaOAEq4ep0dwFS9e5VQVFaQSfEgJICnZCXnEP/gEQHAKRK/yevsNq5Y7mYknvChUCyr15zMBZkkKWdY44XJANt61dFMimKfpLNpGVEqHZfIEb/joO2vp4EELJoh7Lz2KJZ6eT/e7S0iJvCwICkcFuRlP4MA0v0PAi8nR/khGhrx48oFdtlzewcIU0AET5hCFAxloxgwzVtHhdgarJwEIklgohAl/0ifONEEFTfEhBB7FGZnU3t7c2Njdnp2dYDRu/ROfd9odOLIvf2KFsZ3ePngydhPMugb7b2xMXR3PCNWyQj4Osrq5gvbAi2qk9MHKFoNHx2bnF5ZXNfJOdd83gDnjhpzOsphkwguarg7/54sGXz16urO+w5wChH2jaBzJkK8FPNMPGiv84jRgFxoAtwIOorDKEuf7kgmgZHbAuqbWk4jJIU3WgMmdT9anRDbXr9QEY0OBEdYDCHVVqKRur2kb1KX+uOVKGW6sAAj/qSG69MEMpzZWxsnqm3vmgOqr8oyTSuRSa5wLKq6RwS/HwJf6Ahin+2baB/PplAGedSzYQEUZVH3WKPiBhiS6eR+W/Blzy+ROM9VzlkIiQAxgLUAQACgRM4umTLw9IALBNDmkFI+pEQXUlKAGVwiEe1NhMZYzXhb/+8i4LTecvLd68ef2Dd9+9srTEzrnoOmrCq1/vvP/OP/3v/wcu0A2Exn+VhMVFfB2HESjeT0DzWL80POZ1VoASFKGxmqPqRF+FCIMDgiQc7G1MxF+CGMBc31hnbJfXBJiW4OtkK2sbv/78l3u722xqv7V3SGUPHz1s8WVzLEGrYoD3Ndk2vLRrcWnApBq9LxdMrGGIEM3OTaBNT4h1h6zI9iF+IYwFb1iHSc7OLz5f/guCwag5JJW3qMiER6FzVOShjVLcdtemUxrS5kITGSTNn+DGABo54AA8sl5Xi4Tc1M1l5OKPhyYxui4pnEud3jroXt1bbFQUO8TWU21qrkpSTUGl2BdKFZQtWP3xOPUpgwrrlB2hUGFqWpJG6eV29NTUUi9XjrUlRIpWAVjEYKbGAcvywhj5yVXwVQoUk0bhFDZyqUnCDQVkRuNYjwoPkiyYt+HIaWmq0cUATWdjWaHZ8ApezyRELlMfD6U45eiY6pXKeI6+bTi8de0aWzt+/9OP3nrrxq3bt5k+4LtpVS24o+bkt6Y+fPT02b/9X/49kPG51Ee4TLeTNRBl8RH+Gu3v9ybYD+b4kI4yrQTfRmADdlBiDYV7cbN5DMySRbZLTlxjJCgu7+Q/fPxkbX2NsIrtidfWNnjBZn1rE2MCB6qnH/JyZcUP56R3PvDFIAiGUnykJPrxUPLReYcjcA1SvQyTSOlOjNMBYIaCLQYwOJhL3XBHtsofIsjG4sJlWo/DVElJibTpBHs1zfqozhEJgMJd2+I4HzWBR1p5xEEGiygdW3CiWWYfMcLhsIs2F7kAjiPusAjYstyOQFjOHHKqpPJcp2Ky+UYn8+TOC9HgVjTM4B9YmWye0ZGqU2qU8ubTi7T/rYuL+t8AO8ovBlzzE+0EiQuEYGfY5HB9ODZ6JMYUKCiPzoIJ0ZQ3Q2m7EDX5vM+/MLIiG6hhIiesLZSjCYHMKbLiN8xAMmYonMz2ROx2muhqcO3ypbdv3Hz79u0bt27w+rg6GjVgminOCDEMvvPJJz9miMntzxSz4/t1dzFisg2jQMSUYeMTFJI9tbC1M8ZgfH0Wl48R+KKAxcoBf9yUEfRcGY1S/+yXv0aNsYpEDlZH5xhDURejjQRIoOrryNDpgC3qht/Ao0dBeM1yotejGhLlsszwB55h6nxEka/HZdrPeARLgJ+0WbACMKSAFTtZECPissCxyIWicldGCIeDUSmwITd1AoHGlRkToAlUORTiJNLKQUJ281R7JTGo8UQJWKA6vCTN//7jwoTy8zqPAlavOXw+OuciyCWxpFcAqNJIjqpHz/7+3wLv4ll07OIuF29AeANWlfGNFJngkfyC9RYx4HTiV3KnNym0mK2inN8KUTKTGjjKByJgo7mACu8D3DAqPJSZ1lKREA6WWsPwvKKdLOSwiACjTwiHFPiDR0YTEJJID+sLs7Pvvn2HYSCUGIWmTYh43YwoaKg2c7MziwuLkkBQdHpMSIOCY6uoGYM3LEDi64EMwLDKlQWg2CBdCKYfWDi0Tz62UdKnQZaqbQfVr4Bqb+gNnpbZOZfxOBLjWqdcGYJBqZomM3lTh28RnJ2AnA47Ybr8Ql0HdprpZ9gnJpMKQ11pffy1zzAzM7Pyao0R0s6Az7LXOtkIDENNZogyRuTbWHcfPGCkmMpAgTc0lRO4gHVQV70Nwkg1B0NszIgU6YAhTaS5rLCUoEei7OIPKhBFIMgNzIv0yA+6f+/xjQfGB+lDUMDqv3F4e5HExaik3DBjuS/2XK6tlqug9SaoqiTpb4AhW5XH/Dn4KRWaYlaPi3zwiMjjDbiW0ie40IR8cKUENEFCtyWAQpaOJ7AtQ2LawoCK7vFIpbXzjXJYKZAViCpuNq6JnUoymdU64OAxc1OwFbAKxF/+2XcjfgM0236xuzVLVUBQ5dNG2IwANRM4Ka46qw3ZSvTRk8eMSRZ9pU5mFY6OtskDSigAH65loTeKu7+7R7QEFWpFzR17UWv+yQV5oITy4zuuDjJKTGJ3VTMxXlF/KCnUsrIDDEgMLaSSCTiqKQQAk3bNb6vJpyz+dtl2uK4OuVEKzQblwVTjJp/luU0FgDgfXL96heWHkF54CgvNQz81NbF4w85fvc72rii9JeET7iRY0OQTC0ITBCKxNHDO9kvnUDdgIwdksa9EYLnRYXKRWVIiPZgkX3OWLJp4cBcX0kO7JzEsOfkFhA/LVewQ+VF5OUaV8Wum6lwuc88pcAO1AltlK0IQHf/b4r7OTIrpOUj3mgpR1uAjzKLQisqtrMS35COr6OMPFWiKkZmngYXglKCKhU6a0SCHQ5plbGqN5gQDoSnxEXLmj8WZLsJoiQ7LzwMETBC3gGxNpb6lxWtoB0e7RDGs1bGU7w0b0VGeUSI2xSUSuHrp8s9qv0rnF7n6jPjKdTqJaugnsPIoiGfNAnO1IshAbckr51HCsMEkqrZ6FVVhCc734NIchTLebjG5hBpndSeYQdvWCkebYayKM+bmg+SzGyqbB/No7NUDS+yIwEReeGuNMRjGLDmcyEs/4Qr0x3/r14enlxfmWOC9tbdr9ENNPvMURsDShpuTDXjRW6W2g+VhHtvJ2oC3QCUqEqK14/vnjHF12YZWGavI6h//7ILH7SknUpUwgPzNUV0GemRYgNr/iWqlClYNaP88R4mKFI0p4xeEAkN8GNu100qFo+p5qqJ6lJz58VJ55dcMcRdVUslc2jqFJSrRrkAtlVJbssk6kyNRL7iFegt4wz80qTSkSpZn6T7AEouXfJZJ/kinQsVYxhzxZsk3UhphQ1F+qCOVpxOoycJsHpMIm8lmn1BMLAAypSXBqflOJAmAZO+f1XuvUAT6ygWdsyYvzkg0Ck4KrpSV0yAPwyUJYug9Zz93lMFtrxm0VTaFGhVCBoTS4GnRoOVqVQ5GLrEdlJsAnlXTVsE8hkGbZoY+k58UMC8uuMUQb7s9gSVEkyQNDCSR8MfRUro3fs2B0S4KA8zZYgIgL8nYoi+xs7M9MZho1vIVIHbN5yU1VoHnrR3moJlfu3JpaXNvTx9VMY62gvFc9ztQCJ44SxdBW9gJqmFF7Ib1ICwLuXnjOnDYqwlrgXJmRDAaycEgQDToKAylkV/5723Exa83HIIu+ThLLLeerZCn7LVgagCZWWiaJEeUz5xxPGbLQQ4Sq8pGxmAt5KwyjC5CsDcFXdnsIhfIZydZK0uNZqBSbgIhoHxCMp0ozoFMoSqHV3kdEDMmWkpqNEmegluxKQSGD45kU88FeoVYdUwuKhLrDyHBiMTCMFJtmyVVMzIQMjP/ICEhh0V9aB4e4V1dM8SykXM2dOsQ35+dHI7dZC9dvmTfRtKoByPA9ghOTp6/fPlyZZkoHfpQOZSZVTzBl3oMAPWO0h4HK3dkiPL3nQQG+pkj0EBdpMHOLuytwraCDpGP1ghGq93BUEuTwkCDROxBobeyHUvXezTVGKYih4rZQY+RnzQohnHUYB41AasCknTz0jOjV7u72zOteYY2MRwAttplPyIjS8CwmO/zu/fKOEX4Li+Vs3EJcB0ZCPvlGm0Lk4uwAhUpVtsbH//2xx/R38AewAHa2Pm+1WBfDQBQumClmdtpD3cKctQAmogkAhJdj9xTdy5zx41NqKAoWDwNgCTRbJVyFBSFXIEtzLTG5KvAj6opZa3wt47qQYWBNcCDVBNAr3ObLHRO/ngEJXE2q7z111wBWp6WFGL4uG0yV8nWI8oXFQvA2oVAJdAtHL07R6hV7XjCgZxieGS0fDDwqbD1rClhDZaQGk/IgwxxVq7IZIPNe19/gTrxrZCx8T5byDG1y1eheGOecUD2i0d8bBXMML3gSyVAohr+9Hke6LFKaOTlxq/cZuECSBpQg6bbitkTN/xWhzVRXRlqEzSJGfhigitZyF9Q5Yc1F0QZCf0lwjnw8WbbSsgiBpyt278E+sVno3JhlVkwXix7bX9tYnyi3Z0gmKOt4cuiclnu0Tc/ZfNJ7MlwClxr2mh4x0P5iqMyuUzGMYlC7OVrTTxweTqsZQBrbm6eKXfqEynbZtcS4po1JHW9cBuAXuQfJ+UlKcorVHMSqqRFLareVZAQD6hReGQxl4fZU7QCJUySC0CL5JBbRVG89bn58ijl31TlFI2cq+dySX2LSlbVVY8qEAFvUoEs9NTgT7IExYITSQWbkl1CqV2u2ZCSscIrGIRdpglPBCykZ8Ex2YvgQC6RI/lVcVFIldxwa4ERBv7yHwn4yNbH1064jRpZcHp29umr1bXtbTR0fXuf3U10/GyX1+3QMx5jp9l2kzt0MuM5DihxgY9H3HGMDcaIiF7REFpSwJKB7jC5QN2u0pgj/ugbA1IqP/G8PfNCFiG/hIAHTygMhvHS9m9ZAjXhe8yE/MDKW8ToAXqMdqe0hOMh8PHn512eEKBTNzoKVaRLJIMF2sLY3Xt3eQ1tfn6JZSVaKjErlekV6P4f87od1LLlE26eLdCwN6TDqkMGgZWIZqAuAJa3MersjdTwq8a6fNCvN2b5UJW88MYQjpFgXhnFsEAVHkQUyiCCiRQK8SOpy4tKPFqoWSsBmrkkpIkk24XGVznyVH16fXiNPag5I6h5fpHn4uJ1VQXJi9pKpZYC0Eh7Si3RxwoCPyNMvYzfGNX5+tFrzEJnwamcBR5CKgYUuILQsZVHsN1OhaiIFu6WdNJQIa5ESiAA0I+FatJ8otL7lJ8ySh6USAc2FZjOyJFRt+rELTtm0xl88OBpAPmSZyxOEKyJmJmeYRdJNkvl/WFqp5VAt+miofUiS5+hVutPTR1nBo2CR+yX1Wqxoqnj3NlhWUaNFz04YptUxxVQqUID1VE851ABPYw8oEkedvMxA3K0NjY3Jsbp0DPFhnKBg80qh0tEwpEM5dDaQDY2c9LIYDAmEO7aP2U13qu1Naz0A7bE7U9jSdu7L5kLZB8/GLG5ufn0+TPX2KWbD4lyjhixWk+RZTMyV2MovAdLmwZnJw3EiCMJH3nHOo4B5tosjg2ZdQckmPLLBUUVGYcmEYWR5FFi9QgekKp0qwLcah1owGsdq/IC8c3jzSpKeslQ1fpm1r97nUpJfhOfkgaNxoav0f9G4REOqaTkGSVJ2cV1KaShF9JfA4EudQLNiDbAUajVT/seK9TLjwAqsGRdSSFPeFndibv/R1XKwTiWIE+h8EdYiImT/VIq4+U74xH/6FLeuHnr2fKKE0iCIQZxv8dxPlPb6Wxuba+dbyBuY4ri7/iSeQ5yM4WMGvB3Sv+wxasvzurigknHeMCL2lFRZhZo0+huqgIYgp1Pha1d5pK+pW8FqWDOyoEFCkQbAn6tR8+ezc9M0zXHQZOFcRy0FKLVQfZjOmad0iFjNVgIdkJr4zCw3EorSIW8ybA4Twj2nPnrw9/s7Oxv7OweOggAPiyyiGxw+TGvMJO6wcemKoE+18WL2CaAGMhBFQfIMMLGaqY0ee7eod5LgLvfGRnl0HnJiJQObp7ePCJBTjJ/JEsdEfWMUmMaPFQ3SjaufZh8PvDgN65FIKYUiIUTyVPo49KjgkMuS6amlBiVrSD6A2UOIJdSpZznUTHTuQEhyuYyP6NTECvJBURMO/XmHsgGiLrYaIP48M+1ZGnWrV+6SAxuRWQyNwk+QdzBsnhZoQYXSlWKIMCCLmgqx2gj1uZYy1jp7+B+P3z/3b/4q7/GFkEoWEj8wQFvbLq6wrCYjql7W8h31Joxn4QhhgauOFIF2C7g5GD/0A9JsVCCMaLxjg4TJ82bnwd+ftMQu2zDjP7E8qFUZauxn4BvjKI6WkNJAmGKs6Hy/SePbl+/zpwFqovGsy0lQ70wg8EdJiXsgTOQeXgy2T+vsRG/cGEHeyNx2PhAJOtn+R71L37zBd6e2IvBJpotnuobzBQnJKOgghErO/sRKvjQ8DmkTU7YSDNatMLbNCAwFJbxSVPemU6FtDGuSyGzEPKPPIo2cqhEqUCL6vFbHeR44wAYhZRYZQ+xQOAFTdWEqwg0IhZ+qcViwrFYBRJ+jp6KRDDhXOUsmcxcCvCruhWw5uawXmUPg2SuFRdKyFgqAgqlUlHQKlBVpuQNFPEp6Q7BUYOOt/zpdNKXiiUgEz/gJRpIwiyFcJUmmOlKgySnAtp0eEbOMC6J3BqhWmuRZy4AiJBIIZA9PyE04rlaASjAv3PnNq8KvFxepgJHF61el8dQEn1D8CEo4ksRjH6iplGkNr9UhEnwiQmDY976KlvIZ1gf5dzc2pqbnuY7CH0iJcyi033+/BmJaBHYMvQPVSzepqhkyiG75JLDgUN1galRCtvr7bxYXZ2dni6dRVA/O22yipXFTyfHh/sHh/Txx8fZ05fMgKqiw0hGCHAHM7u0tFD7nBYHBoCqRkaFMtk4z0TaF40m3XmduU7I3IzACbHkBlctg3vMyE0KyMEjvALtDd9BpK5iBgJIRULwggRSEio5mmw3n6PIGYkViSoTs4mQpaxUrxa2aLdOImiZESnnHDytflOAkhYJDHLmxlMuzUgGahndepe0Utjn/nFXoeEtxaVBbqm+8dQGjdGzFIw+BbiVA9FrqbF0ElKLtlLVp8rwCHrt2HnhNakkUiIsjyUkW3lOOkABDfeEb9YCBTJCibw2OXLkbHUmmETmSN3EUntpclBlUszVrPPm+rWrlx8+eYzqo+i4RoDgXtn4uvTUyYxHZ0CSVLx+eQ3NqQR3x3M5HQ0C+6KW6trj7VtXr1y9evnTjz+ZnZq6cvVKJvdaX9+79//6Z/+c/VXxwuy8hINNB1NLYJSZ9UAljihYxbiQQqNFD+D5y1fX+Yo4E2fdHuHQ8ury1/cf8j0RrHP/4IhvV/2DH/RhDrbOCBcYU3hQ7ZyjoGm5rl++asAu7CJn5QTXYAmVO5FMN9l3enR5YQ1cl+GWMdUG0+XfIwgFiue4hOW1dXpKRIcwlIaliIgwkfxwMmekqB5YP/fFyiIzBUZdrjsBp1KDlxqxsveaG3ZbKPzitghOQQvRQA6JR4tMuTiiCWqf4iQVVRM9TllFTLzrnvjogUd0QTgSZbeE7OwW5Y2paTgBQFVoa4HHhfoR8QYH0vlnLQb+gErZ6L7Pc+gDBCAonyN20qUgfaGqCOnmJhu55FtBjAvKF4CjGq3OzLYTdo1BMBiKTOVPeGpFhfWOplhbjf1zmapqMbTfZC1P5l4hiNFwvTVfW3Nkxy8zkR8VInpXJxg1cSJZnhDGoB6MDtEgMHvLDKxYcpyfT/Yn+PbmJ++///47by0uXsKo+GASdlKs5eMP3/vHf/yf/qs/+ROA4KZTwgVOHMES5BS+vLWiIW/LmJMo/PHL5/Ty6eBu7ewRnNm66ZIxJgWGBoMzZcCeDgw3fiNarsA0gyHa4qWlyyyT2tnbJQ+wocdmhxtHoux8cyZogueM/vIwSDAaoPwNiizBpROloGsA67QMhKlGUMKSWt6owBKQhhIVGT+pwtNSob9Ux8lozPGKoumKOOwLycjY8gA0q6t4HMUq4tRUJKsI0scUUS0UiuiJtu2MBg4E00t1XnOnIxSyNVAEcYs5paDdnNZpTiE5+G0hrpLfa8Fxwx/JucmjNBcmmLdKjksOSORiw5lCFgcO+ME6+oSAZGbJIsUhiXyIAa40+QeFSSMrCMkQwJkO05QeHUBJDhBxC3Jg76sz3HAbNMRAEG5tgnWLKqrCy5ldv2YyZDUcKDH0j1wX5ubJzVCPfOSgvA19eFjw8iVPasBUSISpdAfYdJqtpG3q6Qyjb+wh+a0P33v/nXcnp3qMpgCGqNszU2zIfqz1wx9879Xq6k9/9jOYDwTGSX2/0iFX3/ZEy8L/BhVpKu4cN2i5gdfuyS+++MrWCl3HnWqiOiuwhwWUhCN0QuA4jh2CWvy5OACK1A6q503/pflZtlyFbLvVZc2CDOVdTfobERGKRX0EeUy/0ZHQLA2NIKxgRlMjzVlqSxIixUkLcHC+xyzMztbc7DRRJXIRMMw8Za2iVxyaBxlRO5kre6OPYB4bLsrql4tQZgZh1f+UIneAgSKCp9OmCeH5ijT1gHluHoqCHqXIgP1bhf8AEAEKicq9LpBVCUtRI/+EE1DgSV1okG22GMMrO0hAjXhUpAT6qBpl4bPuAlDcCLpUyssZ8gcIMg9eEROOsUEcz/GLIHByvE8ptmEHLN1W6KJlZggSlOiTMgYPZ4g4qJpdmVFrAmwGZwBGRVOTk+zVTE5cDyE7nVb6o5evLEms9IkFtYZJMhvuSJ2xaxQmrQYeDs1C8yA4a31sSpAmSLPTNS8sOiCj9kodjNPeNF0MTxWgWl2U/5SUexlBpnaPf2b2lk0AWNjHCk/Gclix2SSWASz9V7fCOx/Svf7h9773688/Bz68J6DIjrt2bPQLLNWOR+YhTVBRBufzyM1D8RCIrZXyIf4RDWWwtbtLOkAMshSuBMcrgCWX+vu3rl+7//iJ1AGFcAyzc8BBQt1GXmHLQrJDpNbiIlMjKwjDzKqQiREDaVahQQOvH0uwuvX19VvXrwHF6Ei8/Ec6l8DC/gCG3mD4ppy7j4jmpG+T30jTEu4AO3QcF6+Jo1KrMWn8CG2j29m2QKaVzQyZd+x02JMQP0cuwk1aSzBneABkd/e2cEUcyJq4FfNlK1ikBcAEtW0GGagI9aJe+jnQjtoR45KBtZZU7ScMWX05M8PKeL4TOdET3M42G+ecT05NwAHGTbCOycnpg33g15mQgXesMeERG4+ywgXSxzsMszSpl8K9Xt1vBNaYnAK+e5jDEFTkDKOB1X4Pzykz9EJZjBELygFEPDExDn+0imZPM3MLliZfSYQbsBdl01C9hJUI1CtkAysoQv7IgLSiCFHnyJl0XBVkticmQAanhsTRftRpeqp/vo0qwlvkgw5w5BSlJwV54zHTuFivQVl0EamVQIOdAH71+defffsz6FGEWgD6HPRVCQMtdhJg3wm+P0AyPWnIBxum8KiEyTfygA/co5kAJmiphMIw2rEfq+Zm2sFaHRjw4cuVNeYHmvWJxjiblrgeG8xQO5ohCKG7j9uhYlIgT7LgOEyWFBURUfAGBprhkVidGorL5B5doRGnCNeABYXJid4MH2Pji9CTyKPOi6qsSmc7HDwBDEJrg6U5NS0QDAdl0rDG3oMAhMipqcm9nT3Qg8DOxPj29i75mcbEIzIOgO6yEkZP4afiGmx9iZpCLH6Ffc9Y+A4tsimLO8ImeQF8/ril6UJ2aBJN61mDUPiUV4Z8KQQDwxRYWjvRRaWgxtrRV3nSYHW+zI2G+X0tnjUac61Z8qNlPGLcg8s8h81QB7whH2WM8RedYDst+d/vXQYb7AqsZmemoy0s5febL6Rz+A3CaAmTttQim4a8UtIBeaACHIGrhixpbhMLOK7h5KqFSWcWFgEJh/A9lVCVqoAdkAi/cQQ+tn2jmG4bgGnDSwbc0xAj5/Op7ePT/YMVWp4tviSwsflqeRVBwit6xiCmk4sEOY8OgckSNc1rOvjaX2nSccnR0afPnq+urvVu3oShsSYijCaumqdwneYR7i7MLT56+JgNidUQvbMGwDDqORPAaInz19ommg9zXM4gHZGEAaA2hmOiJQJPgCqarZ2d1bWNCV6W8+OQYyypYNgXX0lnCDPHDEiZmuTLrj0GmqgAlwzmPOEsEpo+0PhPdCFxUC8X0F2p0gDIRl6Gwz7+4IOrV69ev3yJYG1qepoOO591Y+uB9bW1hENqGGRZwu544TtnJcIJtUDDuIAKP0ghWL3GJKvHQzBs5cOjVExi9NWVi9Ab1YzrYwPjxRnA6WqClaBxwF3JFxpvynX99CAQWKHIZm8Sa5NiBjlrEGgPBwjQx4XqBZ8jQtEwfpBkDgRmBkRhNOWGBkkuRTDGQmYpJCyVzw4MvMVWpdlehyoqGMcES40+kOv8hM8iIhoKVSR5Gg0wXFH6SSGHD8QAKrwQqneGhVYAFMLxSj3UV6vTHvlxvbfocINtNJq/uf/oGXvjst1cPnrAajEeAQw1UJUKQIFzaW9Ecoxe9BZAJKwwvwtIT2pt11bIMnXSyTrM96t7925evwkY4n88OpNuTmeDzNBvb6IGfMcM5cFf0XyxAwVG5IuOLHsmtIvCx3mG82wvSRmeUoWk8tjGyhq5RaLaDe9Enw++enB/hnewJ9AA+M5T9mZyRWEpBR58RvDSwry7OA3Y/SXrbOWPAO082os38CAAYaUtYQ+MDp1wE9Lc8Ybj+pUrH7337sLivK4bHTF+bQ9Z68EMy6SbJaOGGJ6yxNwM5WS7/2VxQu+qexMV0RFwSEuJMs2MBvDfdHnOlYGcQnD/PhSKS6IJJMBBiqIQtlZndh9oJD72GjjCgwoqAhQCgPWCT54KQ1iu1nL2lAPCRYyzhfODW6PbVXALZNulKMdIPS0hyOBOtBLwnJgBEOFUITzHHrBwMwAoVQdXSCLF0mbSHWQtdwwJeYOH8DlsEsM++UFiiawoooHE96MdJViiajAgv3DDDNWaLsLdh09W1tfd2Gh8fGqyi/Apopu080YXhUY6HJCfvvdcuOlvEEb+IGujzfjp2aDLOBQNLt+iRV/RoNOTp89e7B/s14YTOBOiFWhhuwtJC4+Az/JRQ/pzvlPDe/wnLOXkS1L6hjE2WaST6aJXRmfJT1tKfMzOFAAJe+UCMrZrwqWqmEkuLOjh8+dv37o51ppFq0k9a7rnF3N8jLLSm2e0dX1zB3pI5FZW5gi/1S5kjZbARSL24OnaId1hDAX20TdmhJkIl3AVcgGFO8z3GRqENHwz/Ohk0uUlDLyBo+j5irdIR9NVAvWgSkAqVO0jDzWVgzvOOkXvSeceGcp/UiCbK89F+YsSmZg8lZgAaNkQRzH6IURQ1gLHdVX8ty7A+CMCVmkZLM6LKrMZyAlbtDUdesEWHVA/bFTlHU/t6gQLMwQsF2hSiBBIaXYqlCgDLErgRErtnPNCDgrMM9kNWB+peoBKx9WgIk/9UVVSJYzSkrw1p0QAGgBe2boUYs1L80LLYoozazhzXlc0EuW1R3SMInQY2AAOhTGGYs7K6CT7dsk4kaas0ZLfK6MNcWpZg3HndyD45UI2BXKZ84BPV7kemaxr6+trbFpxiXmF9Akd0ZE8sdR+G2xEhN9ksu3yzNzt27du4miXrtBJ2Nze+fzrLz//+i55YIn40k9wHyWNEDMsXIDLwAqx6J0uwOuNzfWHz55OjI8RWR8eO9XlDhlbW3TX6BPyjXi2FsBQNQQ1DDarXjg5CmOx8BEyxTAC1sDi73ha5ArXeMyn6GkZ8WcgRGMoBDWMmHKM131o6WhPQJUicINxMXWcm8RaomnYQEXiP5KfZmmbg+qo5tLCARrQn9/QHT8SwymSL7kMLLScPA2HgesR+0Wtqc54RkYyJpvBJeuwpgJcfIpkSkGYoKKkoxUm2+qCORQGviyCgeoxKgIRtkVOhOn1Q6DmR81KCcDUQnKqKLZUaCOn/6ybf8iWbbbRLXQJ3eZj16jJ8QHt9jnfv6G4fzHl3c2dbm+cwJo3hhlK8uvug+H27g795t5EV25bq5gEW0/Uw0lbFgYOVR00BZ9nCzBgKoln9TZuGJHV+r3+1uaWDBqcj7c7fJUQzw0U5nB3dreowaGIjEDgFYnpM7/GItQjDMLmtlH302YMwtbYEHKfcZT52XmHwPiXgJTQCv22nRoMFmZnPnn/zqcff/jRRx92x7uMT8S0m0zZffLRez/+67/9D3/GNpVndlr4vA21yWacA9yNuMJfOK2JQhQTC+BAa/Ll/Xs0dnSdd3Z2j/iag60kZNu1gj8WhWwtSr9BYcoqC/kid7gmJ4pKAorMc1od3L+Kq8g0nW2+9ry/z54amcKzaZK1GcXCw5AVuzVuijfSAgIU+Aoi1ZlQEiOigFXQ/AWTFBGTqkSwy3UwlIkZuSJHQYneDt95IZFMUiE+jEPT6BIIqQABRiJDJef0C2Eo71fIhqBSOCNuFZZWHadQMEnVsELmEdom+6CO00L2qCmr1hS+W6LR3g53trdmZvqwl8yMhPT6E7JtdIidlNrylLTwJfaMaZ0z3M6mQadEzQxMQZFr37soTcxpWN/d2UMdOPf6fTwygwdbG9u00L2JPlOsJ81TvocQRloLTCishq2FndVPEJIcU20l0F6wpT3nH5SwcgaN7PZ6ztmi/qyt2Dwi+EAZZ6dnmSjA3x8eHTB9xAAJ7NBpEiOiKWNjh3vHfBk5EfgAZSCk4ttOBvBRLL0GDaSRuJIismLi+fvf/R0WQMzMzUUC7AzjwD2udXZs+o//6A/g0p/+2Y8Z24RrNiuOtYRzBD4VV1VdrRZMCMjQW/jFd2lZMFgRVwbUQcHmnpxYjjSrbVEp0JFTOQKnKCLPyRDEqRzzszsPUdoPB6OEz1+8XJif5yO+vHiEnehv6c2wen3AXvyOxzEhgQnAU9pKBoNxFMAsmmrWWn139wBTIaCq+BP3E4sFB3SI4cWCjOeIMxcmwly+oHxEMN2b7G1ubzOYCHztVNlLGkwmI00BVU/Yb4YK/TMs5F0TBIYr5SswzGjZ2c3oLXm4gEbiARwKrgexUi+WTCL8d0ibzcP7E+Qin23qoD4/v4DyoA00tOjL7NwMasoHJ1EUggwYRXhB/sTYAguK0C9uwtHybU/458nX3ltT0/1XL9dQcRwhmxHC+57f/pJq26nzQW+agdQ69owR4ppxuoAAW7DSd3baykyaQ/fIuXBDOmGWBIejIYRMdeIcqrfDh3Jwqvv9G+x8ZWODQoiOV+H5sgdAGY9mYOZo1Y9zyqLkp/nEdBE0DRqN5sLc7OKVBUZmIJbQ6NHTJ69WVlAQdbhJ8D8eRiAjamZneD5+wKghewDPnR6fwV4GdnD9KhSRebs50Rz7o9///fsPH/ERThbDWmdGxFj8ZNOJYUmowCJ3f43+VVZ01iERpGVTTgKhOjZPjsSHmIJtesyRXwYx9ByqDtDkkRKBzshGKNRDh8UqERwCxOnVamzX+u6dOxMM9XBDOU3fQAqlgrC9/T3GbfTT2QcSYAwlq5uVBKwCS2CmrxQXQjBm1xD6bUeHx/CdxMAWfojU0ydNSGDCnEa7i9R1c+vrW3gK9iBh7Qk9E9owxnbZcR/XUuuyNl4zUD3sVjVnpicNOrGKbb+sNT07ubm1QwBEezY7O7u5uUU18Ac2YqhEILylwrov2AhWijdIlAh+fX0DTLqLzG0RUw9x1azvR/vhG+6WwIGlkWRXZMoCjeVXJhebh+/4KNAy2IqfBktIIFiHlwx9zMxOUwUahvydS2EADVvQLZ5l9yo38sV4KEssAmLO96vtIsnBRfDNTTgA1TjwCiHjQ/uZkbLL4HANcEna8QO0AG1nbmgQ/DhTOEZytEXQjm4TaOEB6w1m9y7fuH7r5s23blx/9/YtBscn+pO4m4cPH/23/+9/ymdkC0ZqrgGRMgMNaocXBrZIJetBqR3BMAxVmEJ2qO2Oj33y0Yfsle2MEurV6zJKXV/f2mYUNkwLcJUYxoqejkrQKEp8I/c26ExSuiA2B0rPrIDxCg1UwUPROPwiDlz6v8IPJMsKC7q9ZSTKEVeva7Xl1ZXdvV2+1aAjYvAO9wgSebEOCQlLTXOmBu9I/kDHGIKbbqkxNT2JG6EUiJkhKOPpMy/Jppw6ch9FfuqxGYBj3hA9xAzQvMjGumnXj3tEg84PqGtMmXU6+OkQqgQEyOP4VcSvs8b58XGkw5M0btoqrp2QmI+60MtjuTHBOpChhA5hf7bPqEawYjLYZhxY7K+D2TOdx6JliMWfGuXQC4sL10+LuThrhuil5cqBBLAW0OI/T8KEaAh+vTvRo/nwqzXM6J0zP9Pb2d6D4ddvXMU8sFU0nk2u9thG6PAIa8H2drd3J3p81SZfwBBiugLKH0jhQViAyokACQgIW200mat++PSJgzOqkTpJCM7Iz/HgeHggv+GmJWyKee+eHqA+ggnNibEmcRNsv3Hj0meffPTZd77LsOX87DS+l1dA8Ze97li38+4/+oM//J//13+HrIf0dlAgbV5w1E6MihHqm+bmMG++jEMrSqNKDwGl1WCsWg5iYFRqcIE+0SpxJoj0cUjLBVrhnwwOJeJduItzQCbo46mr8SRSz4089BlIEfGUiCiqQwbzlAM+UhXcKmIEWdp6sde5KlXMnS87XLtxg+aHchoRgqUdxXeN8QKn/WkwsrOaVVWoBHmYEQd+GIGctIrqECbYDFlQuL+3z2ACxFBLcaLWVzouapJaQwpVoKEEZvhs3BexIbO/WCkDIQ7FHRJnu9eIHjQxodzB/xmPgLyzqng7NA0x+Ape3gpAZQgyYdcGbvj8jGiYbDh7fB4+EhaWQV4AARVmoX/bO1vsMohET09YC8yu0QOmkHe2t/f3apcuLTFCAUBU2NkM5SrmSqewAEHELgrfZQVawnxfjzkhZ8T89mu9RicYJBNxMc86yLZcxggg0Z/qwzTYzt5DcwszxfF5RnuFZT3hk36uMFMUUDEr45KHTTo5pHCATErwgEfeBF+cpsMbtFH4YjZOX1pcghm8GsAgERuVLrM2u16/89ZN5vXJYNPa5RsDdM9c809b8aMf/uCru3fpWzJpDSBw4g+7x0mEDZgan+eZQAoTvmXggkgcYPiEhtCusgrkZHqStUuTm3u7LAHI953AESxQB3OKdtSXBCrIIAvYRytpGIiCHNxz7yMcuR6gkEu4A1PUKWzD5UOiJiP0ESRLv2Chnuo8y1KGgBpngR0eYZGsnSKx0+lDg0NwYqEUkSVDTER7YAp3URrNl9YFwFRLPpqgs8H25hZhzNRkj1KApBa4T3TErpUEvr6JkciBYpFZOKMax6loUDgVqutyz7AGcQ5BAlZPVG1Tw2bl7dbq6jpo4bR07U7ASTWBNWvoOXe6bthGmlM6LEnI0AL6TreGcTBG1hn2O9w/orlwIBwnTFawkHH8Qtn57PwUCFEY/ly5ujCSyuDa9SuQCKH9ye60MT3ctVcgcnEX4bOAKOgBVxx9MgE0iA+LeHW9Y2AOpa4+IOSAAKpmNIIyGLj0sOdNVn9pzJXuwkgHbUVWJYk8w0fv5CYeLZJGHYcEj+NwxoqT26r92BJz3tqJSzDkMG9gdudn53iDmaHVlbVNeEjbRSVMk9MwVGtY0hKCE5LlrFgboN3/T/7wD+y7gqJSMzIHMlqB0nMGNUjgC1V6+bwiJ8cIrVFO+UVWJqzG+fza8+VXKlpIgICCaswWkNRGfZALcE2IXFgF71nbwlFNoQ+iVEPMT2chP/KvdBK8BkWeWgXEAZA01wMCWRWHWZg7g0X0nHjKOBXjYqy3Q8mYIMTCeE8b8KBvd6teY9uA3Z1dWlE0gEiTyZB2jbXZgC2tiuYwPdNHt6zWmq0f4memJokoiNdBG/Wx7iCFefKU4hWO2X6wlJye7oPS1WtL4I1qkDg5Se9Fw758abHUKMkAlOZBGeohH/AXF2fx4lbsc6f8+GWFD5SCD+NAdF5Jt/1UXFwWhFMNK+foceUxaBXGkpd6KYukAZUmKFbLOD6aS3K6CuBBNvVYz8AjYLO6RmNQgvHfukUaDRtyFmGWaD66bstMcy0ryCHjsBIIgLsJhrkHfjEEMlmR6V55yz8yOsuL1OwwsJ4Cz50BYlc3sd8PIxD0o/gczsbGFjmdYD0fMBx0cPiKVtfoMt1FEKBy5H5UG3719b13333PhpT1pCfHjCCp4j5mMm74zp23Hj16Rj+EoSdQZfDF+If55qNjcANh0CLyoZFhFJ5OEX4Q94mdUAWVsSqRRpc1DX/zy5+z1DVSELROmz9AyMBkFTeKIFQJ5Z/6q+JoACTABxBwdqYgTyHSOdD0ALNIMQbxiu0iy5nJqSuLl2/duHF5ceHSpUssfaFVhhG8K3r3/r0v7j0kkmFPVTBSTcWAcIX5bJyW2y5xKIGM2FB7OglBhzpc9+YGMJQUYXsLXtiiaQAgIQkk5CG3qhf4B0iIEG8EaScktFheIuSNCdIMf6DKOuU3VfjAC/gmYKNHeQhoSkGDGsYKIhLNLBokkxU6kq0US1kqEznruTiZQuZMAZkqZHht2VxzV0FK6USbkFkAMKdPzENxXkBkvI0PpRJg8FlUeEQoDxmxZOnZ390HMI0nSG6sbxFaEE3ReWDcn1Cqkqk1SikUkI2DggojzOFRflVB3sthveLERA/N83WX/X0+oEFHH6VXrK6zykYqkkasgvW70AtUaYEVq5+lqX359b1/+EcHjHfx0iVW7agMFbtIyj9WM9K9wYYUCaOCTNLTnjiKUzjGJV2Og8npnvIYDMZ9P9nV3uInHUQ2DV4C6/GND24spO9RPhifox9QBklhJa7DNg4wJjvcFhgg6W2Bya93wY6nFOCOP6YFIAx3TkMvPDcRYySr+e2PPvn0ww+Id+mIsZCJ2um9Qehha3jzygJf9WQqxakDtuB2x3mes0O+M8r2EytH5SwlTiUIkMP6QNGnHhYhiQPkgyVP8X8kmg6mPoWDYayGQnKRZR4WNdJH+kjKhEn4HWQA7m8qUjuphUAHtaSq1CyWaQcopOvNDACcA2D47HixS0aLT6UOGoozFtKe03XeY/txJr8AKPzSPTUfysPbHciH8Iyohuqpg1NVpc4qmLjq00bPRw6xD9fW1pgjwzdjBiC+s71vLXt7xvGxw4iWkaXDQjWjBfTFWAGJDjGtgWfRrR4d0yBTXI4WXkEb9x62iuE51wYOWsqwxluaaPTewQG5GPhHFeIJ3b+6FEEyarRFLIW3JpAE7YzcsnTc70FtH+x/df/+78//kOZDY+HAlZSuAL2sNiPL4xub29njQvL5r4MAEP7OQZ3Wq1ev5uZmaQyoDoHzBlD4o6Aijtqty5f+L//kvwInXIIEkgpOYEk+MuHrMs/AJy8dEiKHVKtGXGlz8gDhKOni4iyCs0mWJIZIyAKsViQFTB61up0JXmbli4iwhtYJcKgKI3AUHJ/oz80vXF7adsL6jG5+FwOw/6IAwMqIHMsqISBvdAhTeasnsABIIA+2DETggJWTj8QbtGmL8DRcgYz2YvOFhhXlNZe2kjCIbwXRYGOiDEMxuM4ZSASsJ0eHjOsDltqknvHy45O1yBjPRCQAjggbFGCqZMswoBoPEdzBZzYGpf8HpvAWnS5DusID6eFwfW1zfmGWPJ3OOR/Qg1i8Jqtr8U0wimumoqqNaMFa2AB3SYLIxGYKK0q9kA4anCIU7moMGOAajSXoKDQYh6VXw45DDlvBKIaGoY6L4/0DcKc1ODpi0oZpkwnyw2l1NMqmwy6ziqqOhXMoDdESM7AxL+P0Y2gel+IEjqCENLnzT3HwdRBGF7x2FRBlyYANMB5AiA9YKmCl3fe/8xkdMTMAV2qBZm+GgRRH1VfXKcLLGBYXI+rjv26R6WO61Hw7hzicle30PFl3DHAQExv6DHzFsNu+c/M6X6GttQk8sCR7hawFwRClD2CqOcDUJhHyvy9tamo2E/zh63ixgsUkoQ3uALeUgWzo55+ejVEItxjTYngKW9mmxlu76BoJWsIzaqVX0Bnvsp70xasNuqcQSZRR5Bomigr7Uh6eYB4udwum0QYFA5oQ32RBP98gQjFB0FKSwtQHLsEojhtGhKSEhljafOyhkMABooHT6LPJUtNZNma3jo83cIeEZ4wD4DixTLSE4tROnxjy8bh7u7sA2N1hgfr5DNMIG5uAnJmZYkxwbW0Tb7e0OEdox/gPk+UgT8eatZOwBiSVrisutXle0wUs7QxDyuwIPTvr2DmqTDc/+sUAA02lH58U5ZgBjAxZGJPMVkzSB0fD7oavRkAajQSQ93Z25+amKdi7ssgAFDKnSCyNbiSDD04RcoEjUniIjzk1MMOAu0oZ3qRma1Qzwr6i/sSw0kKKOdAOPlHpH7MH5kJwkI2W2/fTwGjP8WgoA3NrFNBaWOvpdtR0F8dQcKyBA9QfP31GkzI/O8MKNNzyuAMJajDiZhQTWwMyn4NlICL6wMNYRMRK0MXk5L2HD3hXARZACjji9M2k2xNbKGeGg/kUxKRIKoWIwlc0h/nSZANfdIVLCKOnB9mwGn9jSooDAv2ia0sJlRzdhzjlwY8yU04809a1EN0EOHFt30fwHOJHc8ygM9sWEFySRxaZXqkv2yfv7hBjOPNPgCRwrTgoWxXuk5eZmKJ24pTKoyCyAxcI2k4b2w1QHkpIrDnIqNlwD3/AkBdZad4Y/udLAEQjh0y79hq8IkFvjSZCI7D9pW8jDisr67w0wzBpmb7NlFlnembKQdWjk7n5GYZimUNg3trdQ1Qv6rBa5ATdyk/FYorTbh9BMqPp6IlvuvoWOO8DMWLK2OssdKE94psD/gd5b3IdLnhd/A+lpZHBX6qYmXGaj4r29w4QGp+WwV/SShwespnn7tLSPDOGvMGLanIx1jrn+63Ts1NMzbJhI/3KMvBKRRBequNSBVHvObCQ6kY2wlgcjR+o7/LiJRZA48mstjbFuxx5D4SpRhSeqTVky9uOOGEUutP1bQoMT5NQrOoULeGz58+ZtdRvnqGr7Kmq0WuK+M5Wq9/t4vgT7MlbSgEEzLBx6GfJwq9/85vf/f4PsDyKYIE8QhNUVH2fUnCMj34Jqci+cJGOIw/IoYYjavxnLAlzsbyH67StSeE530nADhc84idgFBdRzRRR52I18ksITCxu40Gp9bzpSkvKGUAbHyBmg4aTgxpb4OzvDVgu4lNRY8gpZ1+QMzvelPyZjCOPxYFORTDHoNz2IkxRbnS6aQ3xbeyelJXkZC4CBIalhEY+D3RL62VSiZrxSSBI5JPlCM51zM9PIzC4QS2pTQ+KUMtLZKwLZBKXd24ZroWNsAHl1vn5KYk2ArZJQXhjLReKsFDpjLGCIlOGckA176Nt7yEO+JPmHnJ8yw9JAIdxM1SJj7qiXeAJ5hUZ8p6EQkF+c6v7k1btHYsFVflyzvQivUw7qWBCRs7IERugAx2505cdW1iap8GD0+yXTqI9DlpvPYa8q7xG5A4i1k2q6IiElxDjIKwvt5wcHpNKJIaPm5qcZpU1X52k/1BCIDjJvDENJu6TkUNkCkq0mfDHWgiCWeD94N4H77/HRfAgkT6f1IMPvhjftMIHAQ0SdJGUspz8kUtsRsp78Lxk76LmbgfnxOfUcDfMlYglIXdiGT7vM3AoEw/W69OxgCn447sPHzNzg3eklUT1o2ZyGX5FdSFXpggHSbWKm4c7jouhinT0ZYoxeLijIHS/FR+bTZaL7L91ozkJBxGHm0wqLZwAe40dHWw8u9862j/e66E6TDkiAdsTQcl4VbBRY1kjbSjaZFkrCS5A8B06PMoRn33AB1sm7QyvoTG37+wYXUAWusQly7CokPQUHyMc49RdJq2mukxtruxuvHixzyQrYSbRDgxBm7EN1qjB62jz2erKCvE9qK2tbIAd86BMijlO4JrK7traNssHOrOTiAr2OqwkMe7lD/p8mTi4E3k1bK/aLWoB6/NTLAFfzLI3pod6OrBabWlxnkq5BAIk4wokcEQ+KRUbeGQNUC7PL1+ah1BMgMFqG2s8xfkZ40LoEbwlG6PD6jrOljV20WoSycjUKURV/dQyMkA7H6dhIGorrdApgmSoK6xOxWTiDdXjEzrNvHrITvH095iVP9o5XVlbJx8Tl7hYWm+kCQ/pjOGMgEUnCj7TfriwCr+C+dp9rS2vrOA6WCzj8iHfqkeJHewRB2YMu132S+JDVLiIwgLQRumCSo05O+LN5y9oVaaZUwEmDbiqhl/MDxykVOuf/J/+C97nunLpEjaGMBi4ePnyFYHEoxcv8/UqAwwKhd8MY4dyGYAqFZOCAf7DTAprkBPGCZOopnhaisNw0iMFO7WPnj396N3bCJo2h2E23ABD6AABSzDcPTjZoAWv7Swdn44b/IGoXOYRrpGAGkd7sHdISIVeWlfaJ3iKEqvbdacUEKBCQr8No10UxLod2QTLEWppvmKcgC45yW4wVRvOzk1On/cRMPpx+co8/hmloS/DWBakUs+oBaVHOHblal51F8PhtRuXQZV/TAui8KgA4s26/Bovi9LWYlHUBSksn5GqwppIDx21eocR1ePuVA+K0vg4qKDIfDlbqeWfYChXJDMiAOT1FmCCAagIMp4TI2wwQSeCerhaTM+vzMhM7EeW6CHV2mdTtj7yKQ9oSjmzLIg00LPa4tLMJQk8iH7oKLFXMeM/3KOffT7c2tpWvvRuIYwkPj/AfnU4JuS5a0ti5OFUKS38GaNVtdomw1bTfmaBNw3p4g9W1tZWllc3NzfYe3c4nMD9NTttYDJ7AC5kI4CcnplBadmFW8zFHR76iH/0GJmtuv/gwfvvvp9Gnm1dztB2GxApAQM6APXWj773HZKMUGNDRJP93vjzlZcPnz2jNRAYhMESKBSu/It7MmoKw+zMKxVoTa+fQCL2orsij+GKYyBlKw6XEtBSbO3sPnjynCVAdB939vdWVjcY6CYexROzRmp1eXln76DXP7n9znu016CgXNMNUn51lv20t7d36A4wDILxwEcpKiiEszTC0QfMWFGBMhKQBkgAuaIejiARF4UI1Se6DHlkQTQZh4AzAGe/D3VBZwhFyRaYnKiXcoXrMXtdW5RMnVAkjtj0+M67FHBQJuqqthip2CWlBjAhLqRuUYoiQleFs+6cwJgnEKkhF0lwD10VfXkcdVf+wIEqLkzx1itQ58ViwDIOcXZ6kHe4z5g9ZPRC4oTgNnBgw5Qz3tdZ+ak+uKHKIEBYCCvICYOL+YVMmCl0VQNOULEU2kRAOZqNdjIEQutHpEQDeOoLEkbL0cDSjBBE4c5UEqKSpYWFm7eu37p+/fLSIjLgBQb68H/+l3/zJ//z//L82YsrS5f82khUkSF0ohHgWHO9xnbzdDZoN2gWQAgPSyXhgkudiQbpaRCW48sYKYIJdCXhPq6/8If8bPyISfnOG3YROpkO7C/ML0oQ/6ROliukFCJfyIYi1nkbsrPfSrhDU43p24wTj1oAWXPwy2L6U8cEAaDgGQgZDn/51V2muOkwbW3vuJ2lTTNe02gUTFpj44cnZ2wfOzfAfEuNANK0wAq7IhvtJq8IigbmkXXjVErtOhiA6JyQbpEQlAiGVhJCwZhzoUrKPBRuHilHVBTdtLUxfHBoRU8ZvqrGkTvESbXxt6JEJCyPpQKkDizSQVVv7NtZZ4RWQcYODI/ITC1Ahh4WBm5tbZC4dGkebtHHxhXZTwAIWhaVEXUGiO3KaRCgyof2UGH4nDz66dCAGpoBHBVzXgwgXbosK/cIN8hDOMEA9j6fd0n/EoZwwbIFVhbCUt4/gRlsXr29u43I8KkYCnH9zAzzDwUe57CXc1Q/RlD0wuplplmzcxFbvceVci/nCt/BO0Gv5AyMzz/96IPf+ezbV5m9n59TiI6WuQoaf/GjH/zg8aMnT58//95n3z47PaaTVDUIVKFfECaYEy3T+6JRQHYRlkjyFIPktfuNrecs5CYmhEMyoZrT08dRHJ3RtaOcIkRHOyBoa+YXlsCZB2SLi0J7QgHl5Fr4r/dCaYlvWOOBWtrRkenMgmEbgctJLmfhKViRh9EDRvthFu0gvYXkEg9GFl2RQnmYSCOQmQFiH0UvOfxgtrxtxNIdsMVfuthGkqi2NO/U5C6zZK8xyMO8dZQSaFogdBjjaDTeqYV6SW45LGJcRONuvFtjCzQaVBwYopiZnWFkk7aLkZbNjW2CpNmZKeaeYBxLx2mpmdZhBRFBLEMu3LIYBhUEYXb7wSugQ/R26K/DIWpkngSlZEWdLUk4yoaHszNz9F6IjRlZ5A0VhvSYOmCKF0GwlBKSUVn0hnF9sKBlt/M2rD179hLnzQCu5ho2waQQpMqFQC48QCbSJGZrMyJHZxRVKzpkvwXnqp3rOxjzBTSv0NC5xPqIImGNFoXXNqSUUcBO8MWV6kG24gfhMOrDTf7krjj4rrDaRSoiJgfiw4Hpb4iXuEH2+VYs36i9fOnS4sIc2t8kJB5m7ymngBjBm/nud77zH/7szxjTVqi8M0Mg0IpTpy0BNFPFvI0w3j08OXRhUtZriarhnFqCkbD89sGTx9evXYMUCkCOHhMCYE1O9g4BpYeNdfGITHTaWCEj9XbvyMhADShpz5GfCmRORvpYC3LkZ3zsOEMZCuIgCA41T1hyyWOP7DNsB1enCB9a+FAH4wmeUWS6EJhUulA4QF5mVbo1XtdMPaCnnCBScWQwAVlar80Ck9OYmKhyAXCGLHd32cRKwwgvSKbv5z5UmBZqBAnlkFUecgLAagyYCR8IDP/sgxidJYpofjUXtFIJmNG+IRJaM6bbKEpPdH5+FqHubO8S0arWJycvX60SBAIBoLzmCp+3Nne2+OAcM2VneBNBcoKjz589W19jL3XmhlWdaA4MYVjWDaDZfpxkVonR6ScmZKU2uIL/5cuXcVYs2w764C6LUFYZRL+IbaKlSbIkMD0QMjCvRBRBcTBkESaPabWoglwgQyJrH1E2Rx2OjmMGDdZHwPkyFRVexR5gW4LM3FAaiYG8rswa+e9giOKFxDi4aCwiiQYgKmSBX6AWPiPLWCJ9YiyfcQKYApMxGQqgFNzihng/gQpZrIGg9WNqUcQtrZBnC0x/7HBvl1Uk5MG8ecw6BcIKNkaBLCKOR48f+3bX8SlCQZUoakUxJE5+EcdpIsc6NWK9JUt32mNEbGubGygtpJKbVPlMtTjX/CjEPOIOt5c7+MFMjd4XiycbfCGPxqGz4s4Er3kMARmVC5+4Vf9QWVdZQb+feRusb26gvDDU9gZyNSHrpwHCThgf6vcMTdyVTzvVUHkt0dfG0ybWGWoMQWDDY16fZVCLzgluSpIiQ0pJodR5by35Q4L0WakLN7yPnsgXvR/IgD/ixAYwAG7ZsnNnZwcdIASanZ/BHxwyUsTHlFhdfHhMN8f3Y1hVMja2fbaHkiGlcIbXKemesgi5c+3alfiKI4pgB7w8yQI1/B8xAkaIMk32u8wxIyBIpSXkGtWkfVf5wNqmPM20HBA2/1VNBWYKGktZXBoRP8rHKCGKghYwYkFmAK6ubjEmg67TT2M8h409mW/e3t5eIFBpNhiqp2PW77PbnJ4lXIL9ytJ2QN0gijP2QgjgTIK3bhuBKcAtVQOaMTnwQX78V89hebRK5jdqd+/f/Qe/97soLF+eAixwWKVLLv7BekY1mRZ4/PjJnbfeQktUF7r+RICUFSKWYIBEa7a8fNrp7rNX3drq2vNXr168XGaAGwdMdwjPBVGIAp7HbxpL6HcU/RAdUq/EkZcipUA8Od5+6+bXjx7ixPVpMpR/qi9HeI0bhsEm5p8ZzKfe49tdkSgL6G0m6oB09Ji8jgfToShWJSsI8DUO1IPAihDIlxBUOfc44P1JRp2H9Q6QeAp00imCzVCb7/Xpr8/c1YhhRweRAC4cutA0ghJl0yKduhbXz/DKAQ1u7FtkPUKzJxUoaFOMd8oASrtGLsCivmKQtoWzpqVBgrwdA5a488GU8zGHaIQzGOzt7mP/aALsBRlsm7YFJQNhxMCbAFQENxAjNsBUF5ybnZumwOnuLvPT4ZvTDsav1KZuD5jbohHlGnzAlQ/W0zvEX8YLSAyZpDS5Iy+FbEU5A4mGnl4rL2phG5NT/RRk7Ij3h/oUR22JtcSKdbU9XqHmbVLBLszPIjIICQdKPamu1BWhpOrCQaBqHhSFM36w0lfGIBSmgokCikQwFyxZ9LwfDtge4sXLV9OsD2ejClfRuS8fHodF7iwvxRSvXbn6+ddfITtIYHIGKQBAI0elkHCd3mPn8PT8z3/yE9atsb6VV/hBmEAXZ4p50v8Bq1crqwvzCxKuukqp9SsHljfnEwzKDM2266DuMoXAomhGs6kpntiTReWy0UXROaWJciN9+s52GOjn+C0StJC+Usi0DdKOMghDUC8UmALcAAGOUWQ0mAcgoyx9gwkLpA+3Q4N49dI8I30EU2oryyayg4avz6NErNQ7PpkKUIvbe7YxoRPSGYzhxgAtzdjJyRlZGebnIxSstQwf4OCFbYOk3CGFC8YkEtRA7JDAnX/HJ0dMMKF8tK17jIK3Gkw22NCD8fn56sparz8Ox8CInpvGzyakzBV0eQ2pgbvFXWFLU9MsuOctZxyZfECjYQ6xPqYBD1yCVavxmiipMKc33oW3eCzaE+2Oz1e6264DLxDIa7eM8oElCgoktamSTmG3NCcxD5IDobLps7PveRnI/EmnAAPtIBBeyRjw15DCOTwJPq/wSQUit5qbbLrjMIpTNJ1fS5tB0BiBzQKBPeaVB9gT1oGnMDRyVwGURBAQStfu3oOHb7/1FosL4lwbp0dHlOJtJuilbbl27dpf/e1P0XEsttap01/im4DyxZEedIbWi4HyxWcvltFKPESb9VQsPp3o8GYebSAeERHweaePP/wAkRGUYwTxyxWLdFoAtSc3OEer9g+Pltc3X7xafviYBoGICsVUaY0nJBECMRVS6MByEcMBXf2OswG2L0YuZMXi1aSRskEPA4tGKT6VqbI4dzpdARLWuNUm0DL2nIb72atXtOZsZNg0OGGq/HRvj71INp+9eLW+ujXV69nPUXP8xwEcTv0p2npHqHRNig8CGiwHQjARllhQIhkshm/QoHNFfpa42G6wtW2PBd58BLpHXuhaXJqjVxMHqaNm8RDULizM6g2koN5mAgFhtxjAqE/Ba/ji3KrGzjg64Ol/USkDToBPIyd3UfFgpSUjIZ7wlF4TbJIu3Kh0iZ04Y2b8mIdGDxx5KMTwGTyUDomQzG+5tmA4DwkRlEBQAmm0PWbUWFYADAFSOEJlYRwdTceSWd0PdfBTnw8l4hDIYEL5MD8IigoX8IKqOaMhZCfSx0WGDCqk44OmSWJ5HdT+HUf4/+jRY1wYhdhFzsXV4GbfV1On1itXLqHrDIbOT0+jOjTJbI5jTEFVeAc3pBveuHqNf09fviJJJBlmHGufsI5ZpbfS9Y11zIB1MQzQMu7w/6PqP547W7IEzw8iNCKAgAr5VL7MfClKtO4R3HAxZlxxR67573FF0ozWwyGtZ4y0ac70dHVVVlVXpX6ZT4WOQAiEFgA/33Pxsoc/RAD3d69f96P9+PHj7mfb6zIW+Dn1yy//cPvuAwcUPH7y2ER0m8kALJTDJenIfBeG096C4ULZaSicWEVqsdTIhFTx+IsD69IrJvrIGN08jZqqru6Fap4sKiU5J/6V7IqAgXD/0cMHj3fWDk/xk4w7Le0FoFleBl6FTw6fT3XFPRtdAbbo4cr5jfYkRonsH+lvAxXiSpzTRtyK7xU2XRC3gmjYm7yFZs3P3MnyreJeoNtRfNgMEXfSgcprNtJr1LuVHO82fH3v1oRi296iOXgvLf1yr3pt+T0ghc7yCmEdEg05CXpwj+gvz5eKAZaULGpQh/19e5mA0Ky+YI8ja9wGYQDbWm5vX3Yyhg119q/seju5SqxXXjx/ReMl8LDZxuLe517PqsZa0ZtVWw6nj8ulZm0kd4M0inflPzPXDLk4Fc+QNbbBXC+qh8lDs+ZPlB0ftgrx4YGkiEcyuJxX29a0vEEMmoo1cWQJmyCBUe9f/vmfJaFoq7+KtV5PqvwyRf3TL774+rtbTIo6Nc0TQBwdEZ8K3+ypUbB4/ywusKH22gaFrgtgp/7P/7d/Y2TNAgEaIwM2U5RBqpPk9ZdMUXw9r2WeLlSgJyxi/n0BI7oSjehoZEfXBgMoREaGiwmc+/BCq0p4E6wkyB1guY60MTUpmVrsb/n+/sGT/+mvf1FMQ7xl+g1ZbpYarZ4rq0LyNBh61391D0GCcj54373+L3WbkgzEEbAprq1eHFLOxfIuAKkWYOhrBJ76Q6aP2yP4ammc0zy38fFJ89NUWE6xWkb+EPfP9tfvZuW+2wlWdChYfCxnBku55nz39CoeJ14Jfw46KU4LRsbUnDBVYcB4ElTTYr8DLgXwr2K+dhEKENfhrF+9du0xu/j+6HCSant8UmFbbZN7zdhzioHY2d5++OjAIJPaMJ+M1GzRXrXRdH5ch0UkHWosIE6Nyhn0Sy8iV67znmcPIvXbMFp5TrRRBKYungEwX719ffvOnetX9ye2FuYJjbZCoPHMDz7//K/+6j9IR4T1EkYvjXrBekoJ+nzxxY//+//x3/Gg3669m5HVadHLicWEqmTE7777bn93l2Eg1YhlQoov7BkrJQYPsOwlLfF1BBgfwg3/iFpC0E+dEkySVIMagduleUyqqemtRxHpolBJmo8DRL56Fe/XiH5crjuIwVPZeNseK1pqGrrzzNp+OCl//VZHKRRTalsu2UBirCgIy4OXthmKNRVkw/xVPbtTr+uUtHcCsT+j5iOBmDVfje287K1oEb6e+re6oua7d+zwLCQ3elL9fabwUGiEnp2wWVnvRh6gyq7pFAKB1Pbi7Jo62/5f6EHfefTo4IlcaOX/BJX3BIuMoe0Fb5z34MHBk8dPWUtTFgVk2/efWWgMCkcvBm7N1d6QMCPiYrnpUt3+RdoTZak85JWXBPXyxXOpPcDDQmgANYWrN808K4oGuOCr1zMEZB13zAJVjU9wVHHgNKYawtCH6LywQCHvqLFh40SPQESREESShdqW/t/YoFlnOy9BMq5Ttw8OnrIy2KWGSvPQJ2hjFIxN/vTjm4oeSN+Y4Tt6AkOFYM1QM3Rr9okSZdpLtAQ8pNDZZ7/ZlwX6ZMCmxUmacaza24DQpxoYszg9qCVPUE8rQhhNKUw3CVRWAHLwditcEzniP5la0Q/RDNKjXc9XHJFQVUoBqsKIU2WAc82lWloN3kUp+DQggpWXWws/qZlK1lhdO7nK/4GxI4kAs2Jiu+itUPTQZWJqprSq9+i14xytO9ndhsaoU5GKmeEy0y566NTdREcESviBJLRCNFMaWkMKE6uO+pLWcV7A+/nzA3htbW5Sj+hw/KH5rBE+HB9Mss0Yev/BY+4vK6DRChqxXLI87R1TY5nPeBHO+DDjtmUJZaKTPEGS8nUt4iQUyxuRmyfkQq3ow56Nu3uaVNZPDVNjRIQBbB9VTTXkkWSnDNpfCK94JYcPZvGYI8ti7T/HqJRaafrl3dGTp53SQmhpiLIwUD8/wjX9NJ+t3Pb2pq9LnVbRENRm33Q+NUAMFjxCaLmjVW1JH6B4bNbps+1FTWBY9PelxzfNt3VJVMbqjm1lvrt1+7u7t++3mUO7gIjwwqUcf1VHyBDed0L99o4jEa5dLdcLmtOyikMfksAzaynVXGKbVLu2tBY8ffJMaHuSp4xxV52IXnrfJLPQEdHp5MvquaSY7CBKmy6GqULInkD4jAcYwcgoLFE9qp5QnwXSvRDeEXepdOUJFv9BM5MXxg/Dqu8VQnzstKN0VaBUCpcWDtNYbwYgSZmaxqDNW9Qq2UfrRQ2CqKcRHhDPX714cHDQ9tzjn5O/FHh29zdBxJI1gszVocvHghLilRqScb24vFXGHFYfZDUO7hhJstA9OjSd915QyEZtnlkDJGqpNB6bckHAbEGmNInuWrLwhFw5pr66TbbYRRGhB48OEGTr8iW9KSqds1EoJp9IaQ2jAf1nwMZkHgvtm8oAVIo69lsTsSTag3d+ey129HGxcGwhjnIJSrj1lkoQ5/69h6h+uP5MwApSxglykF6/NunIKBoSnNcHorNMWnUBQCERLRbEoL8lozAKTql1GhRsLK4Kg4Rm7IgCiBhkfnOZmiVsUMs/WXFwCmjW16ztu7q/s7+/98MffGZGeeviJsWj/L/67e/+2//u3wq+PXl6IOgncZFMrqBx9kKdYYcLUo+++errfzJDBbdRcqIsNeorOIxLbP+4+suMAteOVVIAE8GmEqbUdK0tBTYuXTh95hIe8bgDeEltjWULkcnool5EddYDDBHLYWpMPDIpQw63oj1OMlKhDlxbGh7bOIwHL47LfIkbUkTPnhWEfCnxg2GYCrKRRCRTrWF9KGmUP6PoApHf8ZdQCQsUeUgPuhEpfehr419Ie3r69KPHj/WAJtFSU8RXFlor6zwToq88QMkDwnjl9dMX0p5piGLTYGHKVAs95oCSqlW6jq22NOp1/diZD3IFGoT5yvukSBiMZt5lIQ4ePTt7VqJloIoGynA3cUH9vOIfNlsWoxJWED+8CHrVJ7rA0BgaDv3Pnjvz/NlLq0YnLULIRaMhPqQO3iFMd0bmIDvYLfenuipSoV896vdIQFdAvXHjipvK+I2oLOa82mCU70HGZzUMy6PJ453tzYyyOK89PoI7pgdBPVN+0dDZn6krBak5GqGFSqFbUZp3axPE83Tr0sUvfvSpDQ5/8MlNK3ikBgPJh0ZZnvgXf/bzr7659Yu//cW9ew9vXr85bsgE34bKKE02hZU+/ujG//A//o+IScZQZ0w7Oiz/4jtRkvZCQxZoGXXOf8ANfGa6aPuDg0f7V3exnbbIjlcJbbTryYkQ5k3lWKfKBCI7EuY5O1IUhnMNioNdj+FuykrEAgPndi/vfXrzptGVHSsM4eXTmhCxh9e//5v/+Ps/fk1029qa3WNBqx3Q6iG+mKSu6lMxcGkuI8pudoXlpi8Gmn77F58ThDzJEiveWdshfWDtuDA5eU7q21/1w8HDA2K0KQI7YUHtGC2Bs/GHeMJqhwN5RCxZduD4qzn2Y3TbLnHOm8iL5a6Y6iLNViDYu8WmG/grNLrgDhgGzOCGzMjhtU1Hq3LbbnEj6oGm7t3s7PHG6nmDvBiSm9O0SI9yQYvJnDlziajJdWMyR8KOze96lJT5P1ysxbw8bw8lkrz5P0/dnL+jJIt/G20VGEVStmHrMC60T25iyFmjztMmXnJBp71h6/fdCX86ji+ED5KKYFZAVL/qtbh81ULoeNz9+NjEWmeNn3L6zFtHJjsc45OPbvAz3VNMvk3st8zQbpmXt/75P/unv/7Nr//49Td/+Zd/xlrZcR5NigGOEgbg2uqVK/tGEQJA1xx8XH5KUqJBjA99GKyufPLRR+bksU+7V3d3lfz4I7q3YYP3X/zt30nmY5jSdZBjG70tQiVPAVYLXdKAUekGPCEY1pEyOYH2OEpjco+sb8JOvfbqxXMXPv/0o5/95CfX9vc///wz4x4OgN1EeIaGQ6Tk8bOnf/zm1ugouAVJ+4yUR0CAj8ZFaZD574KsLkRWotJlRmWkgbSQn/8gQCdkRZ5MQptFv9RBEvjxYWSNUq3cuLk/nrVhX6MLMnnWgU6OjjIro/0Uclr0CAmyo/SBRwS1pM/Ceb7BUHb12vX9YB5CbJioZy8Shu4h3eXNs/Zt0h2xInpB6w+1pUNIcxclTvEDPtJrSddhGC0tbzYYDsE/fQJEJ1mHo5WT24P0YpIHD2COgUrzFYmjczEADcHyErtF05abCqR+g8P8Nj6e/Fkc19YYBc3IOyrF3UwGZ8LQn2YyV+I/XpZZaCHWVFKrKDPoiIyFJojcS2Sng9WUkgqAJA8khxnJzb3sImzsW2/rCo6L11SgoALXr+6aNHjw6AEzdEEy4JlzBhbIUd3JYsO5zcub7Oy3t285tqbeSJN6+xMSJMqmF67u7vzTP/uJHbJ/+PmPrl+/2aT+BWuzVm7fuvfK0jVnzD55okoAUPGBPOnS4wd2YkYvUjC2sfFxlAuXRLNvpDAjHuKWYM+QPXHi8P3lz/7s049uXMi3e8+hfOWYEyPicR7kg17d3YMT50z9C4Gi4lC079hFC2qETa95hAsWn+5O48vvrFbqH1lKYmlpny8A6tii5QuVnXab0pnJQLURLG8iYvhUZyjlxhK28Qah1Xh+5s7HxhgpOaeoHX6mB1rG3EVCtHwyEB7QtVEtUM1QV53bXCuwEI6ApZwaT+N9Rg0azlot0dZ3izqFA1e1oZYqTtAbxHtDhZ4PcshSFXwwktRgSBjNg/Q/KiUFis5n7gSQOntQdcZmH2Ta6eVYBmkXjguz2l6qJQKO1lWAC004pDycpMZKm7XqlXpYbvrmrYmIgTCpBAxoFjin1bk1DO2piySl7g6wKEH2pR+ao8gw9WovGTDF/XnBPdMVJjG/+uYbc/mbF7hkGgD+IgYjNSv21r6wv7v3zdff/LO/+PMGKm2kqTuPSlNPKEuh+q/+1T+TCfDZD36IubJsQnBt9cbNa/+b//q/dBzEN7duiVuoihORkUi6s5gJePC6Y0FdeSJWDDa7oG9DCOFKA3mOlJBLMyWzugBBk9uWoRigZzu9KyCtS/IhAjYhQ1nFr+zvd8ZZ/MgZGCr5pf+JVD5kyStLVAtjT8DRkSfN3oMvh5PkT8hNuaWNZQg0ZBS3rnJuHaHEf7WXwOdPwpO9GVXre37hPE+qMgAjReQvafW20hpix2ol3VyqWTisruoY6cyKiHKkVyMUXlyqP3j01Mu1mD4gjPtF974HgSSHuH+Jfeit3L/78LvvbiOC20EykubV/rZ5URrlJqhst7rkogIi/dOxkfrRlsAaMAcQsCxojhqM3iOVgbLUD+NO3sXW9pbKxQDqOpCuFQgvLhowrFua8wz2u7bmPvrgWpDXKE8gOCDUOiwM9FpIphE9HAE7tiacu1eJ4UtfPUMUmUXQRFcf1RQ8X0Kl6EwMDN0t+3/z9vbdu77OICWLNcicTGYZeMlLdZbkUo/6VaWxiBpoiRXp5WtZZgPck6ynCE4t167f2P/X/+qfw45HrQY1G3JQABCRN1astmCROvhdfYuSaSJhmE/Qu+DBz8o7cDb/1z4SZ63ElaxGUuE1FjJuxj9fqRaw4DMSSfq4fdoK7IVeyWA//dFabjxfW4DZ2LNo+qwXVl1iRTimw6LLZXGe25Anbc8J1tqDGBI/XJBkCSomJXwHc+zyu5b0hhXpA+u8S7eHnaPAKFLW1PsPd2/fe/Pq7eOHj9+8egNUal89CuJjSijYRWfI7kQexj9G0OdiH6/tbv26vEvoHEnqLhv86RPLqVKxOYPiUPBcO4tMAVx8Q9d6cPBUi/fvP77/8MAEsHl0IMolM2C6fdvc6DMV8ljME5thF+o4fPZKgiJsWBP0hNXgDjFVQjEr48JnRNYvCmlAL5uNg9dhuKQqxYvy9VRu8o4Z8d6cZB71MohqGNSRsMLVPzWOLdN8zKvV5TZXZUIhmMu2ejnT5tfAeffe/ZLF0KIpi6yJHpVEpirzujqZkW++vQ1rS581Fi4QUxc4wHVq7dqN6wcSHs26zL4KhHIYviASdEy5FSMKe9IImqIvZp6SnD312acfcdKc26lRVZvi0oZKTpHclGFcvcAJrXDTS0ShbA+/aFQzWKePHmJwyYiHQRFGDuGjeF4iWZ3Ypa9QIFs2QE/cSm6JYm4OUfuVyoCoat2HLEkHS/hzmIfwAXVCilEGvZOOSFclLxot5DwfCvMH6JSrLrVaDvSmhLO2ijScSBtIp/EbXda7ATtcQ6TKQ9lVYqHhHomQPT14goNAtCrAqrrL2y3nt8e6rT6trLdpNSNmv0NteRGb2AaRxyt7+88IqWw/BzXgtJ2FNjZKbWg96nlZgzNIeCtbySNth7GJjWGVWUJ2xQoGLwo4m2izlzDFZG2sttS8Hvnc+fMS5uiJVtNZcfHcj6Gh6iJh8r3c8T3w+qKlDuhWLVHnoFdD+a3SYz88fPjo+pU9+5bOLmMfdPNskR2caMWZ8xeezTqhy461rZaI1meuqrrPeICxtdsaDCN4ajd6hmG3jo7v3r3/8P6jvb3LehtD6dDsFJ8XrIQWv/nmFlYKmVnHy6LYydTAN8SWAbGmk92V3Z3LerYHDx4YClc/IT1qLZ6OSwFCLybBI2KWFw2H+IloZE7Xty5v/fhHP5TZ+Rd/Jv5gTJyWaUOANKUfOUqJFR34wxouMOhrKRWJp+uIHbnTJ9/FpF3xgoYL+VmiBA1c681D3sX+zq4XdC/DmFn1EnmGOVNn6PiuqKvAElM3uy576rTQDTHWiUeQNC0DKPvICkOF2RukzKj0JpRYr6pRR93iOMoqZjRUq4hpOJ2CLMUTnpHF8eOLmirQm2ogX7YiPivpe+Xd2sU5WFGM0boZHo+9B5GaCEriJysL5NNXJQIE4N69Rzh/9drewcPHYJXYo4vQAQx07cKgX+PvEQx0TTy1KPb6pgW+KCJnlg+qm7VfmJU0ZtZE0nJVnSRe4rSY7OsXLw51L425z8pOjWTIu0Diuu+qChrXPe9ZBRojSvfwYHf3sviJLS2MPl+9ahkd+tjDVG8s2lZIcd0GeK/bf2CCB2h35uwSqElE1IodrpDR5RioGXoWVW/aQYMaVsZ/OoAB9QorNr95pcdjhqzhePz0he0DDSCt0bHwwNS7ZdbAEIhvIcGz5/ZzrxJ0EtaZoRQFtuLRTIilZ9/duf1nP/8ZZulwdEIdBxUbRkrK0D7z8uVYZXtIllbUJ4k113Tq1F/89Kf/5v/1b5lRI3q3zVuDufzj6FSZ8OMc9JLruQunAvUnJO0m8sZw902afPjw8OBAgFZI0gylwO2b1+kMPcj/IzhjDOxToN+QOVc7M5HBJHzfJ0bHpUPWrHCBXlsqIh+M3wNzavDo8VO0pFTpLlmpE08XUQ2lwaBz4NKE6fgEbkVBjB88Rw08s+8IFDUWgIMTwuXq0JmEcDQ9jy9dCvKNzY3HVsx0lI7k3vZBMZNg3Zle1AhBXggfuq1zW8lQF0y1lbl6/erdO3cQiTyZe9GWzU0SgxSgRRhIPLIyojP9Mi/r6eunV6/u6nMqvL4us2T7Mr9vQzdADQjlhqxYzVhcQY06EKSZvg6dzOgzhEHvwm+U8jv2jfjPE5giTnt9exD7VlevXt3LZZwhzf7+LtJ6ZMu9ajkmPWvwmgpNBjv6EoVQeN5eLNgIne8R3TtZzDiSPvPai9eBN33wGWcd0h9sHfTL33/52z/+sZNM9LNv8zzRu6WNnWLDLNch+2aG+5ObN2KbGOvaOB1tvlQCiDn8Tz7+5K//9heWHJwy/m8mABQtYmLVp8E8mjHEuetMCTDi+vhLuGBpFJmUqcNRVCcigPSU6XQb0eiSuLFVk4T5BBBlAr6bpDZkQ1WL8ztJnIDA4aEZ8g1QdkSF2Kod8c9yoRVGR8WJwCX7wl+4+KoVcDO4SeJP7+/tUW7Lt3NMV1dv37t/++6dC2ZuNTrnC3WaJ1Fy7NxgQdHU6VEiZUFWyDdOImN8X3c1rTUX6eqESowTbN2gTApptaeTQXR5JT7YQzwShKpa4Jj1oic0LqsGHs21Bm1nmw6bUxasETlBRM0JIKDg4dsXppxUkI8jhuRqbeXqlR3DdlOnda1rq/IIkMHOUyoulLV8SH9t149rlbm/ceMqKYkZJSTb/QX8x7IbBCV0D7A+Z/u3WA1Mcw7OFDaRuiZanUYFMgjgUnhMKRSZ20EU+fsXI8BQzcMUlGKLgrh1ERminlbGr5NPHBYORpl5dTEynlVDYl7czN8hN/SzkR75KAEkykNsqCUQY0GRcB34+p279/OhY5zW/Tu2JIDgMhxZCnXO3fv3H0SfxO9kTIz9xm+aZnH1CX/1139j6z570aqW6J5eO8NmJwGDbBpVUNHiwTarBRLGkz4N4uz5s6d/+pMf2UaN3y4yo91i8s2EK3mUh6NQIbNJHoa5YXVgrR6JjbLN4+torBjrYuDg8e7o7R+/+ebKzrZzKVDUlBZPNHkyzFCtqhuzn9rd3n709HEhsJ3dL374w/2d7R//8HPwGfGygkZR//Cb39y+d4/NMOgkqYLa+IYWk+SedYmthttJCWjTiJO/hlYTdSFf4FpMk5LOWUH3kfREEEd4AoxqZqeVAzJBFl7jn+JjEmN9TNLhCq1ohelFUhbadq1IxqhcubqPPV63rn9szHxL02ipVBxb+9qpswRJngdXhHhKnNWAO2EAZ709xDKftJdFbC0iwFVf6/V+cPQThnm2gJcS39vd6bpl3l2EXRyqTo+GKIlid+dOzfV1tKJ7tditMQ3zdFGSLnF6Cve2ChWHlNGaXeN5vHt7O5pyr6dT2FUXU657XoGJ96hERWoLvcmDHzu4LU3nmCulFrgXBmVbRinq7N1Op/3jazDnfuwypQ/MxNJ1ouy37tohWec3ZHHv7ezRHYhrG05tQIqz4zbriMgVF0vSK8lsZNIInt9cpsgPPvnk91/+Uc2nL4y5p6UaG44WpHEAliCqatWysKpASiFFrSQhrRvwOAMWAZRhW+RO/fQHn51e33G2AVaWLoIEEBxiIor4ku1rbt+9/fMff/HTH33+yScfnTt/QeRYk9V53szO8Sc3rovv2fCIIDS3k8kI7Mav/5nkTVEnJ9mgPiAHCRjR4oTQI15ejLpkLdJlekf22swGPOoAXCI/UhFT8CYHKUPSl3kzfjWdnJIIjdmzUyUT9FAqc+UDTBoyAGmvpRrztRoMprOaCSg4vaEatJuPNujsSK4GSY5WPZiGFWpUUYF5IVuUjFZVkBTIei8kSXPgwnuo3qmhqmJUamkWytP69iqp4T9BMDcq2Z0apfIxtDu9nAnFWYJp7Ml3h6YEOmGrjeanYm5kHGhrWAUNYU6ABS2MlcB/ziRjUDQ+2lRCK2m7397UEVlGL77Hxk4oibyesNqWM4+fMogtVjUUFBtgKMYnX/DTJkH95vatH//4x8RzMUkDV5OS2nKH1IkL82JX3mflKdK6hcGerh2fPj4jE0w6iVPs7Psyjt8cTgMb/DMrjqrQJvtvX7anbMIkQgSpqRoCIH7fUCK1A6MQPP0SGHGu6OXNzSR7+rLAF6Ml1PGAZK/ubTtV78KN/X1Tg2IdZj24u4qBT/3GA9K/rLV/fPisaqMmYvr1fa+Ncnm0IzxBEysW2oNWSERUfgz9yXQpbrqlHq5Xvhc8hgHainfzYV6rAUv88bRrkt1RFBbPWV3YjElnl5w2zJ0zLui5unp/oIuthJlJ8m7yQyftFvzokcr295uWViJtSXK8llM0UpqN1/M5xwApJXG0Cc9CqX5X1ltdaD4gDeZKeYJwtxZvLvRja8CPiAylgTOlTv4MqAqkCL07TpA3Il/daoV93HEZFst3X6ieu0SE4yGNJ5FoWNnQ08tg09y86gsoI0ivV8lSRzUa35tswgHo1EDE8qukYNA05uGiNcMj8nGK5fZ8yKgGM9z2Yrx99uaNc+dYTI5G28JOG0yAXWdE6z/cvnW74abjdtZOk0lao3HE1gpwGHMVek4AyHSm4GzHcbjvUlDAqZaPHj2ueIb0uNtsqiTqsVEhFuMoUIgBHZkXCDTztonrs+euXbnCUbD5xdEsb7NZH034+EZdh6w7uNa0oUVyo65g4xRtOhzvggRAUabkm+tlqWn6MPtjeihF9Jt792p88aGzSVG4rgEcxnHoODYJqoAjl0P9hjHIISaA6BQ1BZZ69Pa9jfQunj9H9Xs7Ir3X2S2iVg015KORxoPTbKzidoDQgZOcpFHLFYdmrrxBhDe2VdUuuvH3lsm3bE/Bu36Sy95Ys++qBl/Zzsym5xnEUxNlst/xZgPCEV9Z3zxJPjqree/uQxjwqQRq0ZKS3LxxpRwhbWELCaahg+zAmRQq360sPncBvkOpwYiMTV+U3hKASswnEvTNf/+8rVgWTZ3uAlxzsarCCJZm6/AQNeqiSe/xQEYYqEPfI8bw+PvX07Ax9uqaAoSMBKPV1DwNES323fvaKIJQzzb6AAAILPZ3hdNut9krl+0Uf0HqplGvWgyRrcpV3xu76b15c//+Q1Fp9t5SFdILYj1MY/Usm/m1BlRiG0Z6vCCjC2tGZr47ctFDK2nbqZIEIh4mKQr9gtCD2UICcKtQadPMCeOkhn/20Ueff/bRzuXtjz76SGrxhYsXnx08NRH2j7/7za1bd5pXwzcZsB36UjatSkZio+mljY2r+/sCoxq1hYAVwpg0e04rtiju2uWLm0xCPQ2CIh0SoSZFZS2mQwDH8Dy6+9/DDKQZLqbrPdSxjxpUhpsu/Pqh8WUkCreKi87ZWML0XQEfQ5EZAVdNEqAynNGrABsqtoC3U7+A5vn7dx6o8dzGOcnEDLkCJNhwHGzIdePaHnGJ9TRwFArRUfX5U4fdt6XA4XP7tTSDM4d/bgSxcuS0HrEAl6kyXJEzcqFDIsOL8DlybuSTfCCg9vss8uprJoFXkD9hnBz8SuTd0ZwZsJn4C6KRb09JhvIVC9nk7/s+OcrMZymj2jpIBfxTg/7QieviGPJV3Sh4l6TFgFg8ZZL/3kpQiDn8IKgOalTXZul3i7/jAYPFAroWoW5h94gWrvZ+4ptupHWQXlk5eGrzojeivGvvpAPrJd45GffO7dsiK9/cumNIbQrWyifbDwOK6Nnwl+IhK+igrp8Rhh89PGLs6QOuAim1JFzGzSLlp86Zv7WXP7QLMI0kNJ7QnZ0/K63avzZVNXtlrvf5q7dmYf7siy/+8qc/3dy8sGFj8dU1W7ESAq4wifvhpx8/e/KUi9JC7EmdmExD6LBIOJQ+kBVhO+krWuNM12OMD5ARhvWMLuSxLpwbzpYvBLaF7NiSefTJSPYZbsQU/+d2eJCQ+FGr9YyFbmXLtO4k0VFSrJrFNZ2EXiAdpZvySczo7jBBXUymXTBMY8ukBo/tMHav7r16U0IE7MCRKFBoWZZFeJa1tKkxEieVHz5IxbNZt3ZXDq3RabUh8sLXW3lrbqUKSZauzKp5e3dmfJNvpw28M+DWAjs0ApcmQG/57RUXaAhZ7fmquulqxqeplMLL70U8UUtDKuhFDXaVENe6DyBdJ0ORM6BqrF9ZQ7Evl6l51VbD1LZwwE22DD5q8K7XUqQqK+3A9tVvhncFDadnqAF0OLN2ltD7BDqRaElOJJnqdQvdtLb+q1u31u7elXhvScHjp2KcLx3jaxrOS8UYj47v3L3zg88+CVowxWNNL1BkarTVKRR2/PaUw8eFqZcsyOspg2WW7d79ewKJZv2l62fPgMHxYbm3L12yBTfm2Pae6DmqBA2ALiOKVBiluW5MPE2jDtbL4rpx/crz5xYE1uPxHhJ0jtoslx4Ig9NxD6n8IM9TxEGL7Ye2xLfpmMWn5ABCwGdqQ8CYdPLBBzXBdFAffiVPzJseCWjcwp7MUwa4LLdhciSJPd5mPJSmMufy8WsH5zJ+qlao+nulH3JsQUu2xhCKw8NPWxdPc+rRe4mZzz+8Ju4GhDrA8S+8uSJxpoPHdYDX9oz57JAgxsFePHvygj+4s3NpmgOg9tIHNgVPNi9eYJlcmUs8/8EkcpMqsbUODmXE7VLjgX+5iB7uZALDoEcpV58hQKVCtnIacpcoE/2wPHF7PZ8Ke4gCZCQiKNWNKkKFSOJuYExMpvqWEgp1Wwv+jD73yjytoaF6DrAuIP2fKmGaaJjHIz8moOo9EL8VXd4EjAtmhFlx0/cH9x/8z0+e2TpabWz5pUuXT+mmGd83yUagrq2alQOKCeqZvcmI8Pmooq4FJngt6cZUNfjlRxuOtkLMC9hrdLcmEeuiU9jELnkrGWlwqpnuPH3+YjYwNIeKxClOrFjTUdh7ixLNhHQIg80bMYOGERTnBH/5+28KH09TSKB4ZgSpkqvA9o+pY/YEa+sBeb8xm4RObFsWf+l+Z+wzs9wkGeSkZQqRKeY09EH5iIDzZABSqbfv5JVYLSZxhjhrxiSPnVntVJ5Qr3k1cFr18tNBF3tZBBJXPAuZvpcVrUW+UNsp1+zquY3Qhxuhv7y12QHS62v7e9tw6XnwndDC7IdJhv29XY3a5BOhXAgicsY03r+kqxiot6YLJXDW0F1Kjbl5R+kYeIdZC9L0dQYW4DuRuCiKNKiH2p4StSH1Akpo+ixCqYoR7XQGGyo5/nkAoGCUUcSXhVm9p2btEFmUTiDROh1p79QIflJ9EOJbBIu4J3eXv+PpdB+ESJ0lSzrjp4CPucDp3PNp+Qbq9mD6//oKNfjRTqvgNSDOfn5jtg09rSR3SEuL0Ff70aotWcjq9MIs/jFTHVyRgydXV2Nn4cvbopqWx7wnqODxeu8CWu9kDd3GeYtXHZ6UVa6HFdkoYe4tyiGAjgNtgnBmqi2P1Ev6Rmj0I2BVVbhGyHol69RMkzU64d+W/iDuJgL5TucawZRIDuwcnGc0g/oIi0QpjCMl31rbZwPnszbOl3mCxZDx1vqZDvQ9u3ZKENZ2vCj41XffzZx8Bm04MF38pEglx9NPu08AaNWNq3saHZ0d07W6emGO0jA/EL1QIixA4WoqIxA+vS4hx4RTF+ghSrAIjcJc/40VG0DEX5NiSicM2h3hkmIkC2PqzErbDBAWSur/g7jR5NIFuUe+h+9KpwP6qUFqEPNWJqIgBggjVPRYLMsADqqlZZ5VMA81/MIjoKkIT6E4sgwAFicXXzFZRpx+gxzJUWqg2DgbjEYO/DhR7HfCWTsst3QjVsNIydYvesKG+23BVGvjziT9MEj6l8v5kxhSJ/ap4AD+NmWWHs7G5sY/jEvF593FuBLaCIFcbf84Gqfnave1krqbyVmXE2769LV51tjJMyTJkXPlQBbAkycik25mIZbQ5QoDStDcOPrd7//wox/9SD26mrG/zcPgM04Haqd3X7p77/bSR6FpVjic0vuhbDaObSAqmT366SVSnBD7yZ3oA59hVbbFSmq5IqaVMENbp8qLttyuAQrbhei44kIPKITqPfYVXZKLmEwR1pDh8tbFW/fukX6rzs19SGLdswnXu7fXHBdXYuYhCv/9r35DabOQSJqR0gmKGSySNDReaM0VG1SHXWOLT5iW7ro50lMlQ1IvjjlZOAv3PlOmPmiUGQnNc2SgvTLkmtYWKZwGXKZbPa7UQpyeTw0ZXqv+J6LAPI0ODz+mhIZP3qrlRBOZjZTUqF9MNbxvgNg45+zpK7s7i1x6sgxMlBxwBgGXVdCNSJs61QOYc7WgV9frHDOL2qUSzivBqvG2lxOgXF23h7HxlaERo0OADLcE/m0TtLd7+XvEF0H6/u3qh/GQZSQJBr7qMkhw8ql5UcVSX0vbHD6ELLkHVWpD9IrNGFvLfhX6Zk7BgrvVycWCBFl6byeWWUS+oIogRt7WRTre24wwXSIX484kqzBFN4FN5/pw+1Wnx2YfSQtHJxEa6yzn/PW7oz/86leN46Ka/1O9Pyd/lYtCMcwA3JaxRBr0eFQXWywxZGBVj/ShhcuPj54VzVwpXYL4KwSe3oIOWhZ5fAXAlTIdshJ+18+kcrXJx9vb3trZuvTnjtT67JOrV65ysXlOturQNaEZb+3q3v7q6m+NRXSI2gZ2v0hYe1a7mpaGLVrk0rN33vJEA7BEWkKWWZoVGidMCYAeB8ZEbjGH2D99/ASHjBbMD2lD3+YDjJiXa0cNy8nyXjdQHUam3gyBsgt5VjQfeF7o7SRjRc6ZiXanjLWXRAd5zSowp3gZsZV2sv78KSl8bej1SrbJm3fW/lpPoxLvq58g29bB1Cl9evXMUvx318QhSEy2CCTAGU8h+cGE0PqeRIEgAY6p5HjofpHBZBnpF6iAdDp8/OHCuQ0FhApURwH073qDVq7Zvat9YWqgOgeppf5+o3ut+xSaqM040/ZKhR/ZdSNGD7WQphnWeo4V8w8p2xMo34GsQ4XzjNWGX3whzrSsdu1K5MY2L+ILKkV1Asib+PDOFkmfXL9BCJkpwSG+HLtL8Mg9aZTt9tvff/n5p5/YHQC52F+AFZlcRGKSGjcubf3V/+P/maCDfMwGYODCkgZryIEy384g5PjOg/vZ3UqQK6xFjWRw5C8yOPyA9LMlzZAIyo8PrVos6R1uvNkTw/ic6ySwmrREJSa1q/Dl+iqrc21v++Pr1/d2drEBXWDfPl+VjMTbdpAdQcx8YP+wBCB1LzUTWJE8TXMi94FefoD0vn+Uyv4koi6lWqQbVVvpuQ5Kn3D6cPTy+UsSjB8vDh2M52yY149sTvGmlQZ37j4iK95z/sODhw81Lav5wYNHdsa2pujg4RNGQJWPHhx8+9VtRy4EMH3HAVycKfwc1vcfvvnqVhl+sjIfPrH+5uGjJ4cvXjndS3NO/tR5mG+xtw9Tk0Ufq0lZBFKo/dTjfFjHtr6O3CfIx5+F3PGmf5Fo+vk1HhE47D7/9KmJ/A+W8zv8Snmus7lYNZiQwRwcSlzamoRSzAE84vcNSU0EnZBraQ6tFmqjYC5/SZDYNU3WuB3Xy7BwRafBrD9E/KCZTzkYHXrQ4JBf5C9FkG6Nc1Yw8HnsQGEljDdyXeoimqHzRwFALq0jrbN6X714KQaDEYCgNjACupZpA7fod7//0rSDe+h/stQRHPMPcOr84Q8+tfTZuD6hsEeTJhMff7InCYjcfvPSyOe9uw8eSoUAtZOJR4AcqBOLwUQaFQboh5X3TmGRQsnPIbeFlsM8N6kK1+wID6AGC6Ik9Y1RKVBGJJFobfvSluAua1Sj3R27W/tBLhhQXEVstCl6JM8Seh0fhFf6au4MD/wlG86Znq1WEpO0MbF4+eKFr4zo9ilhnNwhMkr4U1ewJDUD8ygT3uclv3hJXu3SY1NUaOqFLeCTvLVbP2vF0/u359rBUsRHkG/nwjYZxRWGEBSffv4JEDNjTZNFe7CeOnXu9avgl9RUncerLw9fSyklDgqwoSaU0dmkqc3iJWB7LzppQ/qd+ZFz56yCeEZXKN7RkTkmir1+tn5hEEnUEHYINi+lGr1OoNDtw4eyJ4BtrGkhteAY+bEsQdDch/dFLg0PXq+/daa1LEDS+fRJ8wkyAAjZwjM1TCt1JSimJ8aG6Sy7jZyIzWDP0/atYfuAhyTxrF8hJKxMuzkqBI6IstPkiVjrkJHdJLARqY/ADvmON9OAevQJFG9E9cOZcwRYksErp6yYR7EdeXM8zH+z+C8tQiCfTw7bZzqxbJaw1TgWT9SRJj8Bawfn/+Jf/YvxdBgA5qUBFmtV/G7BBbycURRUN7rIxNrd3IIFNwYawDfCzwadBP7rPR48Odjb3ju1fpbsVzUCka3GCcMKg2Y7JPfNKFnCcZsYI0yS2NjUClTssFi2ccXgHlkVFgdockIS6+nTVMVKLiria+xFv2yVx8l8NA5EbesgqGjMi2rV43jgi6LDEaFureJQw7ve6tv8io0ViN/DeuwSW/DPIIx62G5ap20BYUSb4zcBQ3ZT8pEBWeIFi9bWRHIRaln+u9TPMKJwIrLevERNca5ks799a2GAofmL549hdvHSeTILKU0DJXbN6FP/fvjwOXMgB0Gqrp10cJdYhCY5Q0dIcJdhxVLkQUSTUcIVs6T7u9vu2NBIpVpXMxYg4ezE0Whb1AsNtCs6fP78zrx7vC0TNtO2MNHzet1QmE9ES3KiZ817nIT5vSrOgRX+SZ3N8VjoqyxO5AGJCdl/LIOKbDSQ7JIH6+090xwsmBUv9UJYHOtVvMXq5QGZ6S8es2olqu3Mz2+cXX1r1cNry0Ls/vrlV1/J4bNWOwqsr9r37rPPPlVHsl1VXHdUzZqmmu/f//yLnxQ7Ys7NTGcjiyD1GVqGgwnuumZ5qe/tM3zw2Uc3T1kywqEhJdNbYQJpGnEso1jaRYfM2WSuWFkDspZbq2jxqVdKPa8bxd3yEBtDexpdx7HhjQhDNXWSMAJ0BCFRBkZE5UpasHbr/n01MxU4ygbwygjlMCByg7+aibetSN+8sdWi1oNgReCrFeXKMKTOJ6/K2JAqDvewk2VNnMnrExM6K4cbnRY1p2666VD0Q27MXasF6q+dsWlLd+ZtJkbcaYmmQ+8EziZiyIm6sCFOJTU1PQeFhG0Sfq6lF9lE3SPAHObnpu+s3fVrpMfY5nil3TpWOkAWwxAjkh3vOKDWdwAeH9+4vucPsIddZaEhIciZV8QJn9TNS9ifqqvFUIQFRlvNYfpcIKztKLkxiYlivYtASQgaNtgjl32vqsSohgqH9InvnqUFFZlWvVExLHNg1I1r10wJK8YgKqBRPjBLRMS9pgZbwyuMfYWlAC77vY2BxfTBI1bk/Ap3B+hiZxnQycttFyYOlTPhjYm/uXP7D99+Zx3Lc76sAzeOVhylM/Y3NEjv7dt3AquhXXN80NK+Gx75DTBGvDD269maUothNCwkB2PhQglEoOHdUz6SpKPkkNVbzJIGb8FnKOhQGTi8Nzl/8cKG/YQwAAFqaZReJcwSpR8blp1ODcCZJPqVLuQQrptfl/9XtWSdksYiyNVGw9/dy9sa9RMHeksLx1ZdYEX/FpZkgtq7CqaAUyiZcDQ8HXUKfHGihrZGag0YxrxNlZqhmcDtgIKr164yHnY3UGu+X1MlbQVH0E2wmC+TK6U5YOpLQSuRTsmPPr4OCBA7LWF1TuhAoTQxUWlPpLjdp9y+Fjn5UAtyOWMXR8WDF6+84K3UoBcDMiJkQzzpfb8hWZ+2jCMLWnZ3+ZxcVtZ/RRXLBKCxmlzoQ9F1RqcazHwgKIIrigfMGE8K+0gIr504zfaMmedamXaSsUCZCHkw+kzjAVExHePPfvbT7+7coQZaq21Grfx+EY/2OJJ0yXaowSOrdngyMyUsl6n0ggKZVTnsR3xzEefOXt/bc0P/eWCJ2KvXDf2Pjv7uH36pboZECtLW9o6juOFiWOuTJjgn+9EjXi5vIgpMKiQZXmgDFvxHRhkyeB+UwAeRfBUKKs7U0skzZy6cPWdvQJqsY6Jthj78l8IjZbgUtRpanLDHMht6wi27srdjQp3EC8GlRzEyUmP5S2tWxVLfaiHbhgPD76pJYDs910Fg9sgw3cgxLbshNuYepZbMycXNDfAgNHFhJBiZ8+eIT3sfBQ/ujBoMFzHAvYopj6oitSrxKK4sZooAFIo4kS9Ps55pQ7/yYieDI3PUHVt6WUl2gQANRoE0UlFAI1M93mDl6scyAQGDvIsoRHvvJYTorYCwTMy3c2XBsZRhqU95TwMGOOqYNubbFBhSKTCxd2+ImSgSgspE8EjW5fKeJhc1wP7s1KaI3Mrt2/fUYOPEmfWLcn6eP88pt8MF516EyiBBwmVnGlDVNWKQ/Rrk+jVNLOhrNbuILQABAABJREFUbpoeHrmPtn7TTScz/VuzyG1Zh3VQkgrKlFB8Ts57S39fvXhF63J99RidyOEv3Jkd3lhDLA1r10haei/vUz9wzwLZg0dw061yEEipOrVYx4ILVqC3GcoHt85fvGAgTfTMk9y+c3tvZxuS4rqaf38s8UlfHkyxRI4qOjfnEg+K+V7b25E4/elHLW/TNpfWCkGqce/hg9/94RuhIRAYAp12rlLrt04YtQiOjl4ix917j968vSFhAI/LEZy87thDTj44SYV31Gom62I1r2eZfhwhs9nqMy/xUHjk7ZuNFdkZdkpo3id6JzyJxcWO+CaIq9a7XbEgd0ubm1vtTaSInzFaWSDlYxsZrgJgUKfoTWTbf04vPWKjCZrRXHhmJblTvv6ql+LLsf1c/Zl/82tEbNoKYLeMOMfO2oy6HUXnk+ovVg3808bIqOpHaPzRBIHAj4QqY+HVoWiIkN1BJpHrZs/mod/gi+CUfmiW89Ss6OQ1QHcx1cvGEFOQiSXZnmTj3n2wxoStubx5WSWsEuJEXqvDn7Wace3CeQKqPdFVwTchH3M7EnbYwbYr1eSo3EAbovncXl7ATwcick/9WjnabmOZDVuqLPfGI1CZpV9tOTcZRFG2fYHylEoQsi0FGUA+o147iaobs8wS3Lp9D9LGFrInTOMKowGcCDMsL14bj5mC65Ru1bmXKh6bvVGHEYWu9OgPX3/1xec/LGdsvB5ljDKA6v+Q5Z3Of0xifdGpqzu7/9v/+r/8+MZV6xhQ3DLFDJjWrI5bF3hxxCdNQHnCVKCJ2vmaO5/vR3fXZap+9c1tVqQkpQa4Z1i6CB0v6X4It1vye6P8aliXQIiyngI9X8mglkHSjmBCr3k0rtG4DohiEzshDx7F2TN/8fMf72/v2p9LPzvHpowbiLGNMBgkh0bqcN/pQ6JmEgQKLeUXzlWilvDr8fO7IDUCpzSIVfLug9yhzcsX0UEF6gUwHBgOLUbx3L/4rkIz9pwlBd6+aBuy1hnbZPfZS36U7RbDm9wCYhSohrUYKxJVbBuAmuvQuEdJUuAmUieXA/p8UfrENveo0WpqrEdU4feoebKYABABsX6PkW24X4Q0X9ne9CSMNcFfPSsiGzudP9VqJO1jZdCK/nEZvCuf3f2Rbq/7aGiABkH1L3e0+v2j9ABJxaZI7cODxxng6XzVgzVFhbgvY25IEXrqJ7CeIu3t7T88eCA+Zo+fTuPp5ELeuivjY7zLO9CNatXcH5lSEQEygIQlJZm5vLpTQjQC10CUDAlnmyg0aJRol0sjg+F9m57AtvAbO9LpXRDIIzhl1vra3t5Gs0LSqxu/xyO0WW8jMRG8lyZz2rdsWKvbaaV1VJiIGbFYcxbG+w9vHx081ANKl7Vv0bk1I78kQTEFRI6GAiYdxtjzPlA1AfUTAvV1k/Oc8DRXwjbHgcwz1lgJJRlr4wJd2IKWZqw15a31EBaKZZ2RCVzwFFhOkxhlMquZo9XnBeOjpr1M1DcvFOBK8vIiFmiEAVoJbvguK85682fPHuHE7v6O2R4mRPX7e1t6c6TTNG7PpOymENCTh8+wTUadg5wta3rw7NGN6/s6sQEvSQcEVIIwtGuUtQm87g4lUodFpPz2L6MP/SjUN1/UpipoVXKQluBHfMk6me4dDXqKgEP4eZ87Klo5wscj39zaMujSL+mkHzy8f+3avm68fH2U2eB/rtsPz6iKSefCAPT8xnlDPPCmKgN6bNd81sRf8PsHQh8oDZCV7WeKGQS/o6/e5kU7tE5aCrpZBH/n7l0p9JiiEoeYPLBbveXdpyzeko1bdTRq/J9MrQuCwQlH8HJDEE+SPcje87IsJxLR9mFfDBB1gynP4ntxqA6eHtjgz8tjfLheaUJT9eM1TN4R+3HCCX8nBBGJS7sBSnjQkrNnOMhPnz+EDxFBZWGFpqen3Vg19Gg+cnXt8ZPDy5e2dAsYBqXhPaLnFLHTzt/d/nBxkVpw5sM6hC/OVheH2chbv0ngROXZNDWDtQKAOSVCdc457m0NJAh3xmlZVN+qrvpKcCYsqgnkjp3zdBEgFJt+p81aXh29oe3KLSaa3NDKmh/rrnzdWxK+Tqv5a0DBs1YwHx8/evSEkSNPVEIPrTC8KF10G4XHkw0Dl/VZ/utRT2sh7BY5b3CUNRmtG1aD+UT6gRTsUzSEYiooez9pHoPgd8ruWxZCiZzsBn4SZQ3UlK/J3N9qUE7nmmiurDU5LXb37oI8v0ePn+G0PY+ZtmrXj5233LQNW40s6QPjihG0muARU/+ADTp1LiD5jdIQn4tuzo3gDPJUtPDguTPnQMfl2Nrc+NEPpA7sfvHFF9tbkp433715/Zsv//h/+b//Gx4zTXZeBDDYayc6LkiTJcN3ll5tbCJheMPRsgPaC2fNLEIv/mAXV8kKzcboO8gYLIhPgI6d0jkdNYrUwz+xIn3t+PzpdYlkRdI6YvBo3cqHO/fuWwrk8HSx5DoX9we3RcCTKliZGwYD+0fsIK0lkj1EIQWZ9KBs9UOEIJ1U3cKry5tWa559+fbN8zdt4ivoZD/KJ7axedYkzvV9wUReMjsN4PgQt2uuEfDFjYuyaxSoXxLvG9IqltHomL9TBgd2QdO31jN6HckjlFMUGnLlPscIVWYtIi68qx+oxsBrK2/lhxbUZ0+qMiO3yE29PiiqAONFrd/X+Qrzw8AZyQaXhm66COZKb1GVyaPWOmbB9SzpOyeOvHXu0tqR05SlKpzBBGndpUzqimCRjp20qAaw+ZBUMESKiADa4KH9gJseIfJMa9VQofk/V/NaRiRQWc3JDcG7DPby1klx6YMXztv2mMIi1kc3r3rMjyZJO7uXEUFhBaQEF61v68iL7uA0rz2azOTpVNiv6lyoxWZHdhi5uTQ6KAxZpJf/+PPP3r8+/Ms///knN2589oNPDQI4jHwlMvfu7dk/P/eTf/zVb37x9/8JJNljCGMgCU73xkNTbM7BYBlRUrsKeXThwiBCwI2Ji4/brrzBFc5aGJn1nN1i3Cer1EmESx/y3M6lHyxAXDU5OXu5Hziw+c7de/ZxI/TCWtwmDobdyKwSemWFgsnlhXwjTzDMMjEPUBQ+clAJ0ac+dc8zDkAVnZulDGTXwo6vb99x6vzDF1q2yEf2CMMYnuF2vLLsqUZwGc6oyfHOA8p84YaGzK/ZH4ofxiJhGjSG+ydlfMUkCWS6bwMGA994OHqyCIiqVMYwEC9U8JmBMBJrPHus/mxGe2CRoLGv3o+XPtxqzUGYIhxbkKRPk2EqcKoeKNiATbhDQ6nxsD/qHB1LaYS7O1eu7OAOWsF28/gi4PDTWIorcgIe45wv4T0I1+SfRGq5njHo4nh0w3/FUo+0pa9eS/JTwJM7vimhHnOyOtUSOSf6VAnvIm0lFFleidTTl3kEEe5154Ii4p/gma8R0G3KgHW9f1JD9bj5pzvfwx/v3ByqasJLmln9/JOba+8Pf/LDj/avXNV/2bc6w0XkjU5yoS/+q3/xT//uP/0DyR8TEaogUX3aQh4mgsQkqbwwEdu/cvzi0BJwbrZR6/KSUmRP/A1eR0b8gRdjyxjIyneY4gsnylp00LGar15bvWg6X1tPnx8SUAaXW5H2IBXnhYw6osZxEpAwzM82rXb2KKZqVgyUMFlQd7RlEP1h3YxBqx8jbsifhCmSFc07KVCYiJSDHq0rAoMouyoMnG6MFRznZ5ySLHMyYFDCsqoN8p7Gq2nAY+ghB/25vLkFt4cHHJVO607FkvM4pKw+ZLL+7LNy9uLG1dRhGsYadZkx9e5IxniTbsXU75lIA+Cb62JqY21rp2k1MIk8jiKFhTVLxDrDeeIoJ1jSzAifythHY7yRUp1AAOEJ4U/pXA46mb56dZ/59f1FfD1RGPAAAUVCq9/+NNU1tEg+EG3Rlmr0FUtUw22zCITXPTXPa72qQBzwV1Rx6mo6Je7aksf9+dEfCxBBzbiah2GXQSFjkB4eclqO7EUCm6Caqlz0HsIygomavz3Co4mGBehS3MFnjx9tnznr+IgiQgGeIEQOv0D+ox/+6LNPP/v177+caF7P2BT2TtP6Uj/ANoBRI3mrSXbVy+2/XV9KFLszt6ozqJqNwQ4NcWRy06SNrp+TJqZkEVL9xsWLQhmGQIaCeh39fEkyqK9uvHlzZJviex9fu8YDf7cuE6sd12rMf3XxwmY9JHJTdy16K/mYp7U7hkBMky034x0o45YYmy9w2kgfdUo0L+I7ZoXnoCpBmEbzMZhWl4Ejb+TNaw43uWac0X/YnTxw4i+ev2gDJRHi7c2LljTwdAjF0slEi6zm/KXK1Ve183fI1TeQjl4FYKP/EbYskE9vRmFNFh7C/lJOEua4EKHVhtY5ZX0KifiMrHvg7b4NGIGyfO0tP3rOYqZuE4UaT+57ACZgzutqn9fnewxN5jI0YAbqUugEh255fyqoKFlZYfBIT/590maYXBEN6dPkjrWn5fEHvRwuMJbGdVyVRbJ4sEmGTLj1069eSkeV4fs2SrYr+AfViqKqRMcO68BSIlCD1geYOFq3Pzc0On+FEwQ4Lgly4i0fW288w0LforfCYjY/+cmPf/vllzGpOmMNPc0b+tB4IKcI+joUolAv7zmU/ZpQR3SdiuaC/khkKVLFaJbKFYNmxK3xZmxAaEYVwIZMwlO8fUGX5eA8Up1jqk948/7tHyyFqXPRKADIPPNaQwqgrgS5t/wyCTbB5CGy9oGCNrJ01oCfPcuZjhCDmKcAj9ZwGSJJN27/RjY/B2Tkqt/D6yEeJIyVzb8CIpFhCcCQbKog8TEUvn792rPDF/I3X74St3xtfU9dyMKR+Y37Uc1QbKHiyc3AmTqJsYs8S6TCEF5a8EJhIgXKcEwPHj61RYUiIn8eaRoA9eMhkzQsd8SXOy7vuzso61HqMiKqgCKQh73fVMqDIWiY8IztBb7gBTpKobQHle5yuQBwDanQb0zUYpDn6KnbL4D0Ei4ur6nQ/IY2PU4X1Oxi/to95PrNqwKWxCtDvrrC3PRkyjmEjtupz53UVHPkQn8OB3xj2CxIoI2qGtPmIpaegNb9AQIwweDRFJ42ixRZz32xcdcEjgVPwQ4FVZFNv5jCmzeuI6WxVnGS/IW60635EGJSaOgle7LwOzJ6s5cVEd7MOCXpU5nwl49xCFltQGI0d/68gauruX/GGaf4SCVEbzSFelgKUEpRinwjfLeSgrWDp7YiP7zaqqUcLEZci+Be0GNAYCuwc/b4TB2FsETuWFIxFigg5eJe2du9c/chmiCdh5rXKaMPa6QlgxjHjO9aglM8fmoe++BxgOSbFELGTpi7UMLs1mjZtEQgZK3aif7o+Nbd+xafSAJ1Csvu5ctiqwE1jYKENRGV27l8MSEbXaRVGklMEyYO0CTDJStj0KLLIo9JmXhkGx90GNkaWZc8h7jMjHwkKUc7u1t8KFJLJPmge/u7qMmI2u1TDrKe99LWZXsf4TVO3PvuDhpdsSeA1IU3/MxTm5e3njw+BMW5c2t7u1tDRrQCfP8Cso/r5WJugWkE0SxSz9IYBdNSJFIuhZm10WyHLQJMHTAOkZQ2tvQ8t8cya8nYRMF8glkzc8wsklfVLHjPdX7z9lV2sAis8ZssgazkomTT4rA7dfWvHsDTtLHWlQTSgDF66zVte0qRSO0SKsiLI3yTXaf0YlVtKCiOUpgERs0SJlz8M7bYV9JBsr2XikwgeGlkjHsjh0aS9RG0S2u1vQDkN0w90EOSKUU1jYnjB7FtYsr905T3GAbjVYNWYouaZLPlPLTwe+GsmIZD0i7Tajtlg5O3F483CFX92IkeLayKb7RzZ+tyojZ0cEGGkAtl3VEdq/D46dN3N64K7OiIAYLmI8G9EH3tnXH+3L0HD8gWuFsxUTSLkVMBhYXemskEXqyFLw+ePPEuJJ+/fH11G0albmnOf5Riv4dACwrqP03TRYT1tJMCBCtYtxFhHEu0BujoyVitWnXLgrIVMpOluGhaEEA3+er10emzr8xsp1OIRgJ5PW/LbLOt9/bOlr17IWKPmFYdWv9lU5Dz53BatddvXqc57F+jm1PZhcQnoY5ic+k3gkxktpFDxA+8ynxfNm5UOvnTfk8zIZANIwvYZVWRgpFjN5Fd/XRYJ4kWJkk2ty7pWkn/65dvbt2+/9kPbs6BrU+9RVUMGB7ev29KBLktzGBkL1++pAaADBjaDVLsWqCoeoLCXIEDJKM7wTrza8Coc0Zb3qEtG3XXSaFYSIMr+xjZ9oBDZ+aLpKa5EzwlvpwOCQnFdI4aHC9CroRq6k3qIH3qGYzhvVYRLzOlHjWk5Cfqhw1djHuPX7bayGkseu52n8iiZjV7Qc2sG2fRAYEb55uBbNM/w+r3H27MMJekJ6bjn6U7SiumC0OSHqVvjVAhH5UWObKeZutySpy34nn886yUpzG6EBGRpB76MKNpyZuzjftMBoXuCOOaI16e82WPjlh0SI4QgDhWsF6nCZaww/1HT9GjzOJSdsWuQAK7kc9xIqfpEwmDMAjM/r549ZJYExNtBdkwc5ydQiJsRQ4SeUJy62JzsayLOH95Z5N8Wo6TSbauqF2qVUBM7Thy5t3rJsXR307r9rNQrbWsgaQfbMtAPXjQk4WH9x8SC3sPowAXeavdfzWHcQAJloEI2UlsfFWV38vF/+o6xg/4wT+FF0TcrQbWlMmXxDW1qafBNLVEBAIhwO0VowVlCZUsb41hmfXzvIiypc+2PMAQgoG8enUnmjZJN5KzmCS4LKSer9iMTkjqT1xIIoIOWr7yOww2E5lSbmXsvrVZ14S4leGitJm+pJn7jw7MdE6HkJsEQnNwV6QtbF62muK7e3eNVAfZEEx40XZGz4tKGJHz+DEZv612zNlxIPTzQ4DmyB8ZD7TykZKYypAT/Vb/PMPtkCNT/6f/w/9xa/MC1jvDxlrVew+f4jw4DDq8rc1YREB0FGU4yc44c/j8kK4OZxmkmY3PnkWa2LO6NqttTj1/a9mXG01EuAmySKPc0dGBzfNfvrQnnmqz4MlTUgI3r7jyipUoNrHb2Wp0rlhVZZCqgZCg0bVrV3//1S2kRhMF0ASWKleTQnNR/+PsjjNnTCdXrYYQWoxCMiEpTECHVYHtjekfwKAJd5gjbtf66TUW/dmr5/fvPJSMLYzdwQjr9nlycmEsZ3+YEcd/WO004d2WOcL37PmzhO+83VTZm3pnxS4IHM5ZZuW02lgb8iLuSdTJZ6RfJ0P4v+8Kkv6TpwMmQKNSlEB0Hz0V8MMahhVBTAAYcYpU6GApfAWAYLuNpVr9OQCWV+xcs2e+PEK0qYKGlVcZwzhczTnpe0Y0nVyYOBSqtaFW3PEWKcGlYWnDgB5NkIAHYmzo98z9dfzpmZUSNNHYa15FzI9u3vj1b3/Nx9/YOHtlV/rbzs9/8lMdl7kOTsBXX3/3f/03/+2LVkWTSUj08aL/DOt8U5NN4qwZWOW95/PYcsq2bU1UJ1LWedafvyb7ApSJRz64YMiEi8q2+Iuf/kjfYZbBwp+Ee2XNciiRWnYCrHlNDbdiBspq3ViWgqtOZBVHqJq9+pLmhZ9j3NgSM+mib7AEugWpSeFwK7yPy5h9+uzFlZ3dxsND5cEuHsNquqnzdgESyHt7pXlTOlm/6s3hE+gp5I39K/q+cfPUWu3AJ5jYjyupi9jfpfP6sVi7sOXYevbTK+fswpkR8xq487cqkJvUNe7i+qSgfvTpddaRl+Fwg/CbWq5/dBXISU5zrvhtIwwJxnuJi8mp08xwRUUONi+IHIw49EiAXBoLaeMIIHl8qN2eaDNxmxb6jgj+RLKTR/72ifuNaJYv87X31aqOLqqjEgkoxTbO4X+fsEalSSxXMOcbwRPWD6ni8Zlcc4R3p1LqQp+oPRBOcwMSdIeRwJv2/Kp8LzSaH2xm5YOX55l2EIotkxt37dp1Arr0saMGNaIiEBtD/MXPfvLVb3/1s5/98Ob1G05OaKC1eVkH4rFSUn1++uVP/uf/+Nect2kZcoU6wNog0uaO0+Oz1DZQAwarxNfiEfnNGqainiG6pP9Z2ySETCGdAmZk4ge5eVEBBGm5fHooQ1uJiiSVkZ2ppIJxWlxwRmymwmuSp5hUDAiz3h/6ZzbiKNm5fPHiraO7FHgIq4KGAujAnfNF+0AczVWHyquJSzm8LaIvCHDt6v7X39766No1w3S+bfMspjODRJ19djkWDs/rmBxR4EwRobZVK4ygPQCtyqDJRCYi/YAULbzb5BlgPOlDCBJobxn35H01JvcXTZpvCafEIyTB4HvQhvNiCrupI8XRms66ji7FwiZrpwnwlw6g7UsXW8bgJkB78+S/P10pXouGLpPk0yVTl5iqYYYB2khGRyQHDgU8xSZ/Fma47R75MDS0NInK9T2P/P2DR0/lXNoy5+nBU/QwDRq0Ua6MZNOgTCIjSGSfPXtmD13hdsdRw2z7sk2ZhsiBmcJpFw4BMh+V+LjsV46gOqO5G/Y0e9Zy8NLD7NKlPaMEYCFClanr6Fj68z/5s59+/sNPr1y55vAvO3GpRLizGiz2uHThn/zFn/+Hv/nFED4WZ7W1k2wX3ies+GarhJevHeT1AthVroo6t8YbjKlpR1rhYh4NtLEsGNwanTNJUUztqGXV5y1fEnVp089hPTAI7+R1DQEa560KMHN1SsYkMQsdwydJSApx3Tn12vCGDxXgTthbcs9ODadPWYxraXw+XkmADK6pgPc68ZGTKLNUcuP61f/0q998c+u2g6yliCzCzHhkSCK/9N1TOztbjyTiyoQbYxN3QD+MiQlR2JxxVwNKb3Y1NAS4L/MBeWC77iozHyIEXa6GTlb/Q8KWRuOETpLcQKoyNXeCZ99WRV11zu5aDczYjQFPPPRv5A//1J2kRpoRgpVV0Tq+opEP1QaGDxx1lYdPX2xddgpEG6O8ffWaNCya17sBX/r+MDuNjmuOw4oNgRFetWO3NUGkjXXGolnRIhBs4dvX7x4/eU4nw3NwRxYDG4xzoJdZBabXSMZZFiRra+OCFfFEaPzJsW1Dn8FcY0lbrY2zBnhfq3Ro7sIj8YOHjw645urnJAu7CLo4mSLKDUeYJQdd37xxg1dc+lNHywk5RN1wBf3a6kc3r+9u7zx8fJDTkFHL+Tf4dASYLTnRlkrs7OxATu9EssYfU0AEpVD1wtoF3HAIQveKvnCqjQdmdhDVUZ9ct+aTubSGzZ4uTSCHEv3ToaQbMrktuejOW5sOrAgmEAOieTKfMvSPDXzira2LdIYMCXdKcP/ko5sXzpy7fk3Mji/3/rtbt2xzqTbTDzTKLbuxYD99jKSsiGGNNeRnzjx6/FAoWTqAp9kgIjQIAEYr+zs7v/7yaxLhAeUcnoKoqZ+oaG/Tl69Nj/GI0EK9BmSwPFHy6EmgUDnd9krU6ZNVdslIPnt8aGSVjzTbM+ahCXqw1il8mW2MPuKAdl6MXIdtDHyR9WVfTZajqVKqZmVFVHJheawCshtiyx15hlxWWtk6WaybSgiB23mFjEo+Z57IOovnWDl8X1ndgLXyJ3Jel6TZYD6BfxFKCIz/NOgkiOjcRgEr60t6gg6f1WdEhIbFUp19SBYQjDE5PyfQ2NBHck5u8GGY8k69WR+FMov4fw8Ek6wAAzOAudRawPgspASiWxxFID1/fmh9L7+UzCEiNmAFEQ+f2TlXZLl+JLzotTDImKesWYbOu1evXbll3DwBMc0s82fEwDCMUB2+LlP61asXYAgexeL1wALAXBIOMMMYf+kkrtEfbZmsAEOiR7U4GEba4NOsHWb4LSoFTCTFSmF38OlkX79BCpUIMamXnenXzDsmqfNRKXTIqHiUE03+/Cc/+fjmdSc3snk9ECx4/+7ZUzNitFc7HzrdgXieBobAnxTRwK3NU6dt+tJh2kSvfxZbW8mJH2jTiFBlEkM4lPlc1iK9bpPGxmARwEd/1WZPckTkrGoiNhF8swQnWm2j9jpA1OIM1c33kr86tZxRTZIh/sNz8+Vs/MWLT58/47DyHN0ZSbJAR//55toN+w2WFKABr/CJRZCA/OpYqnBNyl8y+LbAikQ5fFIG4QhADfrgu/nOMr6MKxIOod7Djev5u6DF483NTf1+DNZGIua/LzmaoYQg8xlPnVkoGhOuCW5sAVKBR5apg5XswWH5i4O0JRxcsBSGir558VLI30yUa7XzDEieMUbC4pw4m2i8f+/FSFrrJx+t+IxNWNoayOogu9B+TJwa/GIv7IXTjgHoHC/4kwwouVS4auFi4kX0llUDPax1C3BBjkY8vKk155aLsxUchxVDbfypIXKijOW76gA2gJkPttXyyyBJ5NIloIpQmezSK6qB1CtJvLmDkYYkjJEG88hP7+QpOcu4nVSSBn43MucFeVMVwKZPOh0CPbxJZ4cxNQYyvwnW1kUnR1r3fmZrY0mI8FJJaf6xMbvWml3erGkfLadtSJMGZ8oTk6Tacrsm+hw12YygVXkz8B/UMuSW54mWNSJcJFxNGRNEBWe1ONLd8VADdvtqsSHjgRIhamM3IQuJcs4ArWyA9+YgkT4MjqadGk3yO9v7rKSaNsdmw9GBjWewL1jrCIne7pcY/M7uDkZwA8CgDCy10o75jUzkeG7YWdFkaAIw6gd3Ry5INScAzyygkW9r439Ko6OTe0zJ377l+04nHbDK1xqWRKUwheLAHx7ozG+eTsA3QiOiysj5KwT8SjowWqr/1nd3nEksnAWde/cfEVzLdEknQptP8I/+SCi20YtQij5KSEcTKWPtolJMwjafuQx5/xIV3+OeedzcEPvgUFoGS+bzwnCSqmQ5pDAcozZi0942HnHn/Db3op5Eq/BrlELDm9ev59lJkVjikBR++EYubGXt044FTczZESJR0gqZs6Lx2tWrN+2VsLObtCQsFhTwfky2ndZo888GE3rqwcF7CfYYeIevae/NxaPzCIjMbg6iLvtLWmgITtte3jva9hkOJdDxKridt7cpyo4teDXUK0iK9bCzSmb39Wub4CO9f14hBISvl9WUOPuzKnnr7fs333333cWNzc1VKVMrFkF7LBKvAzE99+DRY3oLLIUXLzlZVllxJLWl/BpwPejHxKarT62eE+R0nuw8wFIwkbOsgIj1EBcjmR752BZSPbOJ02yNWDJC2yu8ZVyQisx1DoAo9shCBkHq/MuXITATq2bQUBqFBuAjjjiBoo8Y7GYQhjg2a735x93dHZvQqOTsacfWNVEztEzutrc2c5BMS/Vxexrrsg7B31CNEwv4PVC/aoHiRbv/05ndvT04mn7BkU8+vZmw2B7LRqg72wvxl5GDsAHQpOIE3sqqNQxaASe+67GWa2+OWiwY9C1QPYx5Qw82QFgn+ch5unxx4+9/+S0DBM4cAb+t4J3c+BORKR3QRCTfrROmJQ1c/HCp/m7p3zLuyYMwK4GhCurVJiG2g6i0jI+u2699nwn47e//8O//+j8mRGnjinEPFQIG5WEe9XsZilL36KkQaG4QJgK9na0Iz9GrNpORNnfw+NEdp0cfPP3oxQtz4Fx4vrvXGlKvTObp+GeqBnIM4dzroyl5bF3AjixM8LU9wZ/blB6BqJ+bHvgtfsOm2oztu9v32iLgwnljE4KoGFaCf8SjyriGIlpf3rqzfq4pZY+ePJUjIB3m7YvXL5/ZKE5nMa+olhEV+19phUYOT++vOWCYKWUQy3f3ANGbGl9bvbBxkdSYQQ6gikpDT4wWTDNBxy1Kdh4cP8caOlCTYHLMxtglG6+pQfLc6yYckw+dOirs2XyhkRU51CM5GbLq/ac8A5PGzxHN2q348uiMGQm8VlVJHEor2pmFZrWJblEjHigOVjpol79pkbpHozCotBR36qBCBSWLNSlgi5y3HyxgP332vLEHsciDIiBgRnZa0bKESrIdA1ExATQYkxwo7gd7OgurIJ8BIii0V1MLin0bYLqnct+X4AGY2VyJQ0V1HNshFHZ2CY7Fcc3mztozqqkVBxm/FjmkQ4xtsaMxlMPRY8c4SbjUT169sn/t+hVm/ppU7z3j0EsW53MSpFF9/PHNB48Pfv+HP9bbB2E8NZAwZEVGLdXTWtZrEVa9SKNfvQOCnfr//u0vrCIgYfocp15mndBjfXVmMaoFPsxlwWL4Mq4fjiBD+eTPRAbk0WmI+ywRzkqljmbDxN3+8Md8NQya2xFyystiOH32wzmet7DWUrn7nBZetX5+VAYOq8aU8sDuPfr2F7/8pUexZ4ZBifVIg94R6+ALSuMeU5ljANhI4lS7BCuJ8+JwTVkU23Y0xvAz9Qsn4lEHMnwFqUKNq/i2ug9PNzfPIhm3J2PC2J/hj1VsNEHp/kUBSQYkofXbGjOSaUgHq74pXbUJhwsEAk+ikvz55NuA19N2KyKbKu+FKTXtKBDO80GrYcu8q+4ktEZCWsyDrNvjTXWzX4u1YDgDvJJP6/HyBuNjkATY4D5VercBkocxVACW7qnV6jwAzRoGDfUJ/FHjnBedOfRdwIaNHc3UQ0V0n9mON9yssTz6YGXmzt62HToxHTsppLYiDk07bg3WrINtahJPACAHIyopkB4e2wv0B59+bHnJf/mv/oX+2d6yohYyQThaxmnwObd27vrZc//Vv/7X33zzHfd5Js5wsBl3ck+OiQT4qQRPhSvFZX3zWlhMP/Tu1P/013+XDPYYo0/HBiGW42NDNEEOX+gGUKR5+0zXZg+FdcFQaDRAgVJkbwMVxYIaTn2a00ZZPmp303vd/fA9thHIdZh8++1t0BFPv/Ua2hLWSggSJwly67znX/72D5kY/w35T/rTZChBbBKgJ6o09OE+CApwnGqhu/HMx/CrgWhFMaqbaXhvES83U9X6rQpXXT9JjJLkpLs6ZX33wnVl4J4RWxDGxgxbELvRPy5lzSYlbsbG/iQZwTRwzZ3eGoHs4Um59J1CdUMZ33zUNoN4L49x9GfGmkiKYjW1iJKirvyabGTpOoVVxpZL4kTh+/ce6CD1VPtXd51PA06JIflcAyJb8/TgCeujM7TdquGBYzukThnKo4FRHvmopYELYcCWJ3oSjSHz3Ac3cSSrGT6w0x8Nn/iZbjiM+Ueff9ZyQOFzzpvNTeSAQW+ohuTcMz0HP9WofQQvkmEBUAmQjuXTjz86d2ZNNF4AxsZg9cxTQgW4OAbm+Gc/+tHO9vbB08dvPliw5pCDNLwFTJjZPg3yUN5a/1knyF+iQ9a4NaJgBrIOxbCRK1K3l0H56BwPGQVJcHQf21ZCS3Eb3Y1VBqi7THjFMDK0BN2TBC9ZBuicMuc7GeCzFEgU0UY+hmMt/79Et+irIGpcnxFD4jI9Jnkw4HPgLgQW4dFIi/cRpuEyq5m8KO67QRKQdICIuvTli8yDiF1SAKrMljdcBO3wPsdXw32ZfwubUxjwF/d8/vyZe5bm2HEta2G7lJaM2nBKeLRXADCiUZ0BvGoSQLTwUIobp5a2K6Q1UIKhMkZr7sSE2ox5WiuC2bskTT/UCzOKGIubu7iokt89GVDhjKC+64q7E1KqKRHQtyYj0G4yo8JxKtSFczVpsYiZAjIArDdAj8VIoZAVi0yPOXVzaniyv79nrzeRSQs+1SCzUAIQSagHSpv/BApkwlBD7oZggHWrK1CZ024hP71Yu3XnjnihqKw78iANGFJUMokKiciKsKZ0B4K1dr4YKPrUFYZNK0R4oU7re/ToLgEgv0b37oODEadO+oexFNza8x/duH7v0QM72BY9HjAEXF5blZ6nVF7VKbJ59nQTWsViBCc+NP0WpVWYfYzb5BjU/BadFERKrGgtaXEPldKugJpgqHfdgEBcGInEC+quNmiLyzjANE2IdpnM5RPsSlBHJ5EVlKRx50QxSUNduqo8j8EJ887OrkosRRiFjgc+SyfGei0DrETnaEWmVlH/92/ZEGUgI6n7yZPnsq4MBy5uXazVYVXoVk9RyKqDOUEIuQDoaT2FvwDK1OkPlDExBG278ehORRgN+qEv0mcATeWHCF6pYzR4051iog13EfPy5csirQ4sQPXNzS17EaD7pQ0LUA3V3l7ausgaPRC9WT+2tnjmg0/UExBs8VA9vzwSAxAQwY5Q4x2F0YjLiZ4wXYsHFGKVHDmIs4S4Y1TbBJsn2R5NOS8fTN6pGi4eMSYQ0ZMYGya6rLSDMIw3sKhPouF31Fo4URmuVOApnAUEWYzTcvcxVy6YFWHm5lR7cGCb6cPz/JnpkonWwDfSoU6W1zTKeeEsFBplmtEjVqhOA/CX8P/dd19RJM4ekyhNys15FBNpXSbi+PjKlStQe3NM9D0vsUDvQSCZfj6S8FRbFhmtMRdFNEOHDYEbm9S0FOdWrbpBBLQAuQ7VAzg5DceuJ05bmtGhjoptaKrSivULZ6guE6355CmXMfFyTYNtZ0DnkpLIM8akFkhqrOGoOdvHYvmcIuTGg2Hw0r1Wie7ywgXR9ycmkqOtmoGZESKpLAcV1e3gIqJrWp2Zo+p2ve78bgvoIGhmimUFBoripr0FchvO2BlXWvWiAPF2FCzY3AM/IknWMHyanl1nCGHpmec0QDekyqrq8pkzRvA2Px3d4v42NBfZsMzIW/KcxQbaz3g2Jrm8v3t4aBInPXOMpDzFvd2d5y9tEP/2408+Onj2BMGNGsEB/vjJ388o9j3i9BsOvkVhZFTiT19ddO3WQqVQVbCibmZH1s0zvtX6waMnW9sXDcDck1ljAcadew+v7m+LT4hFvvrwamtrk3ckX018kTvaum1LujdshVT/gzI83jPrvJ2E1VckG0jojBszogT6yrrg3l/94m8fP31yX16nrRxevgG/3VZ2d7aQLmjT6HSirjNY20FLF8TUED2ySyWkfcV38uNzdLS3u82kIH5RIBsIcSTe8ZrOWASJ8rof7eorxMdVhzxDqvS8guDMetSo33W/okBEXEBIY4BD4uhEO4IHtqXR2icJ9K3k43bUhZN+vkF5BABC5uc8zVdvtjYv9Q0Sgd67itW7ZTdWOvL26VOmZ6HVCb2GYImDdZgmd0zSTQFKbBQj2jAZIDUBf5pqOPG7P37TlLvaVcpQAcdowGC7YQqtiCc6fU/9JC6JwbGOXsWEctMGqfPpQYLR8ii+WcwA52hRdYwSeRs1uJAe6kzggiYkw29q52mpdVsXLJdTWXKQ69grqrZNkg8mIb1h2Lps17FnnCWuCCl/eert0cv3nGARM3oV86WF2mjo2TPhCmqv0UU8EowZFCBaHHNX2x6msck40fDFf+yg+IGBp3DJeY8jI6KKx3klmUUzO48fP7t6fY/DbfKO6/zxJzcVhJc87IvnZNS+ZCBsbcQNt4G72DEmGRPiBL+c2NUea7jEjbnRMTm30V2IT7PBxFbi7/vj1X/37/+jYQa/3NMmrT+8N3fxw88/g4g7MWsk/gRg3YvDls6etQ8Eq28AjYZIx9JPQ5lPSfV8oft3H5zXe25tRXmnnDT5kBkKOnmHL1+8f/sqwzZ9WfeCM07wuOg/UiQFPVhpM/uR1VNcStAAxQia4uBqZF1dF328dede+6JKJaYrSN0SKBMfUlaePjh4cv/xk4ub20KKvFvaCg5WHjWwRL+oXfUY5jchxWTnB4MNmaKaZwBSwIyVgk2ynEEEYORBGsGw8kY5Q/ijq/tX0kT6VJ+qgqK3+jkkgEgDFTsHNthI/QChAYWhBRub2JnDikNwivJJxoREqupPn0wFtkavYOsq9WIeimBigLwtSR/8sRHs6pYO4S2HvMv1J/eQnkYkyZ6+f+/RxqXzdlN8fHDABbq0uelpduTIDsEXIoWdrcSVQL5qG10nb9uX6dAN8I+01SOBeXiVSAVT/5PvsFuEaIHV12g6bAV/xs5PH0xDdM9KEpm6aKMBjxqEEHb3tnnMIKfqZgw60/J4las2CS918tLvaqENPmw3xG0Q8Mg6IO3CSS0gRDSv1HT1oICeiioBtY2LG5d02qdOvTDxhVxeuP/wUaEWgsISzwljS1pXqlx4pt0gWYclfPS+3UdjpBOdGxWV3HnKxOXXX//u8qWiomdtO27TxJn18j4xgJH5Zt0+AAA2LM9gDVlwtutaSqDHwiQqgD46xTr2wlA44mVhkyfq64CqtiaWPfby2EJhsf8HDx/YANjRL3BRYGf3UMvLUGHIsdDEby+pY80OchIuSHBCzpakDwFIjFvpwi8sJnP69dv3TVVl4AvSkxrDktQJhXkgRkB2HHrxOv8gGo8wpBiMQL0NJOPnnOJD4GpsGhFMAknq+6HhzTE+VmV7h6WH8ltjGIxRpZFmz1wm05SGrvWWAxtcSesoDYpZs1bpnINOVrZOG3gQl03F/qSjINnevmRKUVUIbD0AmrsI4trGBjNWXimQryGgyiNUAG9kAqh+wPDyyFbYho4/3u1bjWVrMr9Lhd2biIK/ah9OI5oyEIN/eqRsHuVJJb7qBlBlhdGeKKrMv2mxupLprEJRk6FMALAyi18wYHhfjQaE7Vi1gBe22poHKglYnYkdXTbOc6HPnzfmblgi68N6Wl41vpokpQnLCAR4PjXdUZFnsZJX0rda5vDgRuLkK8J88vFHf/c3f3Xv7h3bMjJ2futdrUmyU7wE53v3H/76N7/93Zd/JOkxE6BkjdIUf4+SgTrQarMSjbRNoJT0H7l67Bd6zUh3wDoSh/qH3/329TubdknybsJeRdaqjEDqYk6XNzTAaQOkEEjPkt5KBomw2qRwq18/U1PECmIDilb0dLpd+wFKSOMkZPVPRm/laDUnRlvOnOIgUb/ofyIW6vNZSD4sFpKbOilSJIOJ5T5nrea5kiBgywDdtbj1GTmYiQYwpvDA5kuh8eWDPtHA/2hZiI2nVBxQqYjXZ+H7gnoO0lJeLZzPqRYxhQHqiWq18tOGW/WZiiUxlV9d2TJ7PU8H8mrHPabKO0yGsqOfYVHxZL+eoSrnXy+ESwWnpbqUsWvdn+rii47z6aMDAx773hoGHb5+Ke+DQFfH1GwlpyCmXX3lIAiCaV64wvZBJsVswW8dD/IOvIjiw3WEynIaVe2FZdDVpnICGNKZbt+9qzayaJzqHQsGza9d3tSuNSf8JTWgP/wkjbua893W7cBplvkVSosWnjrfMW110IYob98aXBkYf/n17XMbm2vrh3cfPpagSnPu3Htw587dx0+eqEd9OouFU9MbR/RkgH5ExTiiTtSpZVwQO0JAF8nUgkS5vmLA3Xn55tWX333rcR2cffbEgMOWp8VxbMM9Axd9ghezcHN2iMGGIQjLxBI3ZNDuEEWzoc35OyV+zJDkToDDb07zAytlz13c4Q6lyA63s4t6QS1vsQmG/Df29767fT+5mepAL2dIwghK2WtzirVXJhTFgwaTROHkE5f/dKnB2iVp8CrlsiuPF/lxNZTAxjBtOGWVGV6xkr6q/6Rab4cXzZm3e/2kvYEw+SYRMmF5yTxAcYWRENXXOiS9ODZ1PKLp3BMF8/GRLcHIeAXkcGXqHuDiYTAG4Mm0HX2oJxxG9Mx7akggGY5Mgi8ZBk12+LnVQpgle9woz3zuW7wdmJM5hyxeu3nN+lLRDrNOuuKnTx4D7OrVK/fv3z97Zrdqp+IwiUJEN5eJqUlFXEWZ+Uxvs7uz++ZXv3I/B7jenPK85yDduHpF6aAiDEZipxsvQQR1QClJ7tnhY4esueCNlytEXUfq0M9BwDu7+7/89S/vPDagEG5o9zuDe3kxplDQGtIRaRYwIqUm4OjFBfK6gDETuXYueL/mRswHJJFRNxwUOcE0iUABtdQtIaexizuETsY26feWwlySbAJM+NNHjTRiSc0IL8ySmY6Tgntx23NrJnGK4lEhLFFbrDm1LCx+IxvMoAIoAkr021DBtCBiDltP7e/uFoWhLhsb3EpLF3jEulEnRDx+/tzgXpAS5ME/MjDGhSSUR0nrGDP9wyL9yoRXXBk+emVM6yCeqT2hl4erNr165WCysxfOSBkks0OfCqgf8CfyP28yH4ycS1RUn0ecNa1L9xdD5AOKvGpWQKlBU3aweI5UUMDgtwwlFxc2JS1/cBNsVi2qp1yVWAHWEUDkwyoqOGpJBRYhHiTQtBFZEjBC6VcXXqiCrnWWPM02Ii8K+ZZPaAdp0RgqjgoMHOONBXzCdFUnXtiRxhZVx1T8RcepyTcVA0m/r+Lkp6a8Mz63C625YzMedcl7e7va1j7BsrLipMZ3P/mxuI+DNbWIcHIORJTbI5KMdULxmfqN7a2+1u80RkA1/1CYE/n5Dz//D7/425cTldQi+xl2smgv2EXFILvkotx+zhM/P4tG6bxr+tVwpdAOarPu7kBBzo5ssRrHVa1UIXcpedJt+Yv83ipygiGjKn5lfqDLnnkkuFRumcU95JvWNos+QoKBs0LQzTbwemcjDEvgjUlM+MEOYXlRURL0JNusAuoYfDsawtiUrcDqSgIGeCYXz54RcyRGpUK1kMh23AcGYc8O28oPxem0Wo0aQi3WN9bprKfWhZy2e/ve/mX3Y9pYekEh9h5FErGxRL2ggHeHo+PTrMqnFTXa291F3wcHz5Q36LSsRisiasZqTzqp1g55xWRALZ6xL0SYd0SKbZHSnCsAXgggFsQD47rXoYPuDhqEZXTEG1S1LQ0T7SCPi2p7jI4Ize1XVbXNh0wsUA6oivQ4vRgFUH88G2UOz+gwwjnvqgNBxCeHEUnJ+XMX2jLh+MiZTNTVphs2CTKbJqYkjfzN63ePHj6+dEmgec0yBjvBcg20pcohYyB0XeNdZBdO9CGqztOyrWY/UBm1jXwXcO7eu2dlkp4SdyRJC7MpXucYmuopYouhvKn3Z4iDRNP2AaET8VV64pkzn33ysR7g9SyCy/QMriZ8kNJ8WbYgW6OzMd5YDvwsukLw9HIpff6rxLv3Du3s9vop+yKdWtZxJt4Gg8nRgpPSkdlPeOIoTrZRh2GW3rtIiHGCLsFaJBuYrJ51LHq8pMEQ8kaZTuFA1d/YTMGIlvZEqDgV//qvJI/vVJPNX379LR6YBaNCser4UGdtV20D9GcvnjlLS3aINf6Okxtl00Kqoi1OV1RqIiYO1fWrmE4Xn5ELfYkZECTBL7dRzJtWF4TvagdARcSR/f6Mwxov4ioz6jNwJkN5EZru3TEpaKKflFJPP219HDWlvjAcMRRmRQQtxmF4LFdQNz23lyvDIXAsuwb5Hrw90LV7Sx4XVWZufdUiurHKsSvgIlkC971kd5FAhCroYri4xzgnIxHzKy72SkxPUHvDHaL84jnne9XhcTpYk6cXLopc6QpK8MQusV3bX5w519aqgFc/7NSIwWXcjlCQsS7GtdF0F9hdvzFQDX899oWWGIub0JLJaC2BLMApb3r7+eGz546AIeHBlynI1nKJI7xd8dhW+994w5YPI81n1zkUE06E79Hx1f0951L//uuvGXfOjqnJWmN7OB1vbXtc8q+qG52QDkluZ8odxi8pdjNcsSbMTwdJuvnaePe9fqnMlAXHodmYRpI0bjp6z75QDd2iZra8jpKgW7YmNfq9U7SuSCtYE3g2crIv9JHRpfsIQjqJjtwmQSfcYACqAnfDOh4Z05sKAaq8VEb31v0Hhy9aACSNw7jKHDhH1ut5X0mnt5uBgcHISKYgUBL6KnYR+U/EIbbQqLqFjrVsPJqFnT9GcjRTxBAD4u/U0JtaMchBjZlMcAFShgUPkMFfkSOdCbqhAqpzMAXSsMYEwrvnLxmSsxvnCVa9+SwufW1vhDdvBRMNsR7cN3H2fscBR4FdtfZl4zTmiRhY6wgnsi60b2+lOFpHnfYmdMhXlCxx9h2Ai98/jwS+SX34hr7LwSR61NKiQu5110dKoiEjlM6cP322vV4mom8O1GYzkU4mEgWYt1bZZsGZnBO+JYwQZ0it/Qqk8mpdjEb3YtLyCPenkiOWwrX9doMPTLaAsGLPUi3bo+T2FJgnUYjJVM81DMs3O39hI9YXM3HI7OszdR3LAZOdNCnO9tMvfvS7r/5IJEitRwJdVAQA6E/wCT8d0CZv87ETOAk6PWP/TjVbwnUnb7YZFmRX/5g2o5CBejDK9kARDpCHIsJl3Cid4tmeSOUHvQiBZtDaYPfRk2e26fVqMtrOebbHCyovGSDgolbJN4k2btFpKAb48oPow/RFTnhlvb8uP+xOQmDQSJub+cfxRFxbQVhwc3bp6isw+524LCLia4a/noLc6Hj0fQctYM8yXNpsiXddnIOvnRKbQ/nWMq1BZ6me45GjqEyo1+dUr3dxKPl+9cbcp/lXm+cPURsRhdmHo83ti8Xm3zvIY3LUwDszPjYpKU3yvJ2ojz9YuDvu6dAxQ+qwH25VlKpRkx41qGV6JdQOltqfD3gWzig8Bpm1Des4P+bJ0wr7ltd+8mb1ff8Jo9GoJLeyi1dD71tTKhziJlLoYhmsaFjM0TJAW6zWOzXVNNO9SuFbE/kzKTZvdc/LAT/NDDC+JzE2aDPNf+vOXcFyadasniETE3rv3v0vfvi5gAVDhZgEhQAQGKxe/pl4sStwFoD8zBpDhCYVvi5y+NMf/+i/+7f/A4lO2bE8Hwfxo4EOQdenHMlP+Bn7Ji446k4faY4vvg5lcj7bDNuKqHe93Mezqhu7wN6T4LqsqFPdMeKEhlMUD4y7/W5hyqPHBzubl7wMT4MFXqYBMtvNSVcFXPTCDKq1P6cudiqHulQe+SI9UTtFvBiPJ4cyq/Q65CXfSzGBSzQawzDIAqOeJDgjNNJXv//YMkMU34KT/nBVS4o2HERBcuwBpfMOIO3mzTaoYfALjJS6JPXEIrgig/bdnCFmm5YdX3aW5ognqQnM0obf710xjV7fIq9CAxACDvhiF6fF8L/ps+hrs4YgrlZFCiDWcIs3QOJ5GAWIhrYv9WS8jh71MA1N0lTbjcRBZI0MddMnFo2IV3op1guxMOGovhDy5ocVx9iISgsM8fS40QamBcaqhLn94KbShgfSqyzt76SIC+eYTxbadtnQJBdVuEjKgpGKR0SmhZOmlgpF+K7t73Gtbl7dv3ltj1bcvf/gP/7tPzx6/IS1plF8Vz4bI22nlFHsE9ZK0Dp49FjPiYBOZEQy7eL70rZvV/b2r125cuf+ff11y2zVFQbJSYlmhMhyHFGXt/ZCMP1l2ByUBD+CDHAweHfU/mKWlHz80TXukoGs1G1NxJagiYshmw+A5PPiaAVLFQ3cGIBm8mlt1Vaq+i8jnjOnbCtgH0Krctu84tmhg0OePnh8ePacOFIJiTrBYQomDlQhFv9MdV2/uv/t7bv47esiEYY7A3GCZV6iVuvWjUrLu0YXwgoNKRDqmj48UN3RxPyi7eJxYh0q1K6nEAr8/mi3oQQ0F6l31deFx2xiBnSMwwCcAELadYwqrhoiul8CLeZbpEXLRUtmGqjGtLbM3OXbwNOy7fYlgLl68aOWFqvtKrF310dQ8snBU32LUeM0puG4YNwphZOByOyXwTpqPQCrfNzGXtaWDgldsg9whN2wapFRFvDlGEsPRajYrDPnL3Lat7e3G3c5euOl0bxh/9rzp/bgeb9/9YotXt48Lkd1e3f72aMnNmtKHMdtw6uaiCJ+19lCKfp3ox8Vkqn//f/uvzGcacX5uWYJrly5am7tt7//UijFsKQl9D6xbuyjhD9grQsfnWPCWGS9CE9eTaEXzVo9nCnhVG9v//7rryK+p0Msf1XF5eZZoMAw1JO8egwJxSF711FJ1l2zCzdvXPsXf/kXjQJ1jtADz9INUIyRMzdGkwbV3qsiOBf0l+F06UKJ7Mb3xnlPX7xg9eVYFYN4++7w5bMXr9440lRNhP+6FbrRrnWPNX96OSXFbvoop05z6WvX9/cWGLrVveJX/YmaA1pa1JQvLGGeQICPtjDY6kbJOOFdLQzJhkEDsK5+oo0VMeOv0NjXIU01+RkCdZkGECbP8kfFT1zg7qw+i+ko89bR67LqVw3Nmxip5bqaaW9FaMjKrJd0TzqkgAg7SzY0Kwtze8s4dbadzdSNTOswX9tfiOOUDRJA4JBo5vmLVzp0gU6WUNDQYF2d1n7LZpQoTkY3L4qCmOeiBCNDMyOROo0Gu4lH6Rf8k47MyLDxmKzLJHv+8oU8GjbEyBz0PB94oVKUoagCDG1p0VyvMBcPJD+eep1qhwQtmGqoJTWP2ES/0Y2FVd2Ei4ez2tP+/u/fvZJ4gTHg3d098+knn339zXfipBabYfEMwTL5y6zsyOiaQZSQTJrp/JocntcaNTRl3d6/atSLNkjUuI69zmfE+kRC6zjh/zhLjYhm7IcRSBGbfTQasbsXvV6+eLlzeYcQCviAg8mWeju0zCIqM4qTSPQROpAwa5H+3t7OrGo8Z9DHUN17+OzJ4fNf/+EP5AbnDAGjPGmLrPlppLNK8yYGYmAARCfRvCHWjwQfH3MyrJlwamjsI18IowtIajP8MNPhwdfAgxyoAFweFRnwWM2NrFKIMec4UTOYYU95Yr1xsaSabg0BvJlVCK10bkiXwLgfpDyc3u+nvOl37+TbuU+r3aWKZlypPX8XANoXVHOiLlvufEOqwc552+aiGrh3554oAhtr7yNZt9rSzdniEygN6k6f02daqdiq6NFNrYirWMqnN2dS2BV9GhCRktwnro3nzZ46BfCFHmbg9LyPh3mNKJBmT+8AgZEM308Mii0OHFHMV33/1h4Cwo6CGWqG6r27D+zHozlHINk+3hYeKjFzCiTun0zygwePHC6K1JFwqu03cCDjx98hXoSLlJxV+0EthmANFS9Rg6LMZzDzxo1r21tb9sb95OZHGe7kuHwZyXC47qtWhLN29vfv37kleIvHL53+NKvGaSP9fK2HbeLVZih8zvrnPobL2NF0LSswKgGkRgsN3kALLL9HbZAkOi0fw5hHT56cWrbHIBJ64ZGMEEXTeuIG2yMdx8fYs3t52z9htZevX9y990CmtJgAsqrueYPRxKJszST8REzdrKMSQrVFUiu1s8YwyfRwdIaK7DTwbGRi/uX5q4M6d8YEH/AfIoKvdVG0Kb57llp8D5XoQmzwSQHdztdHWtqhGq9wcIsGJhNqCPGMSfPfQoqWU5db6tr/PO4kp7LTaahtRXyJwZD2pFroGv5u27eiNMQmpxR11qjQ+Ob6hhaTDLXxMZzpvX7Osgtwq9r+LtQDPPoBwySp2hahP3n8TFF5DQ63HO4M56jhkRQvxyG3CyDITTBwY2xJb7AHBlILWO7DyuvIEYZDFWLX15kOQnNxOzRMUBMzxeBUT4dChukZPlublL5mK5r35zdkvJlbsLqaUWg/NW4YUKtv3VZlGSNLyQSEKW+L/VuYFs0j1RjNQBnqeV0bnvqQBb+VUhsJiINuWg764cPO5Usf3bhx7/7dFkUue4GdbrcUNiP9KSDLQL93zvbtW1+/eM5YXGBglXz14sXW9i5c6fK9+w/IHwwNLP2GL66FYdddBSF7SyADFRbDZ9e5xowyeOrtlTSY+M3vfttQsqfKyUjL7TltIzFxfTU3D2C/jZc21C+GeOfBw+/u3NMvAZqJ19wsBVW2umsNFUi16vJb+klGO6ZBtOZV2WWUpfn21n+G80SuvIITdMS42YED4NCcGtLdcKCW6gixqJ2kU6MJyNZUKMNcDIQu0V4LtRd43Ned21oicOryFVZDhvP5od3bV3Y7tSCH2281IMzURPn8VbTbY0t7j/FkaY50AO0Fb7ntBcYb9T1aYAVXBiDvqYbGQped7ovjVxhzyyGNoGQKvH718u6rVxPQGg83wkGpsWCybie8y1ucgfAfld7opAhusXQpL6GTiYczl9cugTLh8rJy6Taix15ECM/j1qpnMiIQCsYjBd3Uqm7Il1Z05a0JfxzrInzAia3cV9VCiMpF3+lQOIS9PmpV/aNhUUnLSysBsoDT70rODb3oufO2A0xW3dMEx+6jjz/++rtvmQw+DznRcxrcBh/7qJJm1lcubZzneD+4//Dq3nWW59KrVzIKXv1GiPG+UzRFlp48PzQ9j4MBmSgsPnBALZ9wdz8WAwVGCfKUzuNkILAJzQjkr3//21P7HYtG3F9QKTM+cvr0hs5kswjR/hETPqtigf1qJIbNVPB/w0r1099ozEqod3lBHFY8CevA683jVUeT2LPRDDjO0jTj88q/fefoLcApxOMxASc0AdJG01G/2pNzhKmWseh9X7A+EdohdwW9wcfwYkAmkrGKaUyeqqMyiXbdDMD7mVv0o8ILjys296dQZK2OxuXJtB+4G0u5UIy46AEfPnhEQFOzgVN575JXCBJIHlH2tWz41dnLsaCGuI3myCtkQYsASUngpIICr4Z85YZYCGEjsKbq4PJh5/z2FLZvwHTaiXt0mbQfdfAyY7Q7C63mKedzmXUfckUbKoEghuAhGvGHIqBHPbi2LcN4816I9kctcOPdaUlsH4oiOUOrmkGdCuG3uqqu/z4eRX8D1y59sS2VebEP5jmVjjRrq9dvXOVsM+qXLl1u3infdqjtAsxdciDPnj638Tf/+L+cOXNLkqkyugKZFKAVTWLo6E/D5eBMAtwBgAYXwoJmIPN1zJO2TZ2V6RYEzTONd0D+DMPsdnnqv/mv//U3d+783S9/7T2Oo8DZrbt3T2jqZeRbmkjapSlPiwQ127PMadcyxdJwkUuOWlgUHQudNlUH49rde/dtHH1hjjLXT8uwcEqV6RJvQkLvSccMQliLJXsifQoPLuNJnLdOilGZTiByFwJSc4hBXw08kIUQUZ8SmX38YG74jaBWk6TdVZ8UjDdGY2TapA3HVCvd79+0txTLwNYGGnXY3FHbeZjfIP3EGpBowV0EH6fBaBw9kBull3qmQLXxfPiXI5orp8xdZFNFnvTD1T7K0NgDjev/ggKEffqb3U1VvO4JAQnEhKt3w98l/mT++zsqz/iNBZhX0Gqq6qZXcp4nSUwkg6fK4bm0tUmTTTvODEYypF3KIfdUlsJmi07fWq5FSWySxjBCxbZlidwJpAHkHUK/eBUegdnvwRReWgRgTpFwLR3Gp/Hsj22EfvPmtcPDZ0ZZRspkVaWC78jF5GBq9Zw6dfPmR08cJf/mWT7I0MJvs5PGOfxMbpLCKM/h8Toxw5euiB16FapE3oQ4261LrxPg0HglrwSbyodbhhk6wL/86Rf2qvv1l38wKprV90QePMAufEuyAyBPo6gCFviFoB5Jn/I1kXEzU55FikMLTB4FQ8/NsN2+fXt/e/tocwN31t8JbqpmBumF6mlULLYciZbjH7qqQz0B4KOCRo2LLwHdLgwlyIgWKjXluA6AnCFAz73PNF+5sjvUyZ4p5vey4Veg+VLcOJdrYD7xn2oQNFODmLR6aLq+1D6CcbU+ppK9rW3tK6DyeTRQ98JQST2yJxYPIyqpcxGR5SLUlrZI+RB5qbaqSNCxDX05xi9xwBG3kFbDvB5ycDZ8YlMlYgUACAKsRnp3CIApMWRwARgpiApHdmG6cPT8pW/Pnj7d2t58+uSZYryUAWfFUmNOgZl/OkBhdna3D5+2ByGHkGTJFGyt3zQUiasXMItuAx9o3Z1P/thcuDOP/BpHhU+CV59/9snf/8M/6GDXj2Z4YMmd6/Xm1xhZLwL2yv6+cxX+8NXXiABpzCD6Zjzqh9PBsr+sT84htFNgHwPpxm8eCW+eWz+Hg+7IOaSKxB4oCRBNcxcJ+GozteVm0292ZrSHKaWHBYGDHeQoQXJGJdicaB2XwykT1I5Ow5UkIAjLGSBRdYh1BGQn4UhEPKRJB88O7t2/d/qUzMQVsy3jdtv/ue33vMRGccYshaOg9DzEasn/SBiUSXv67jPwpPPMnOesIeUiO7znhQvKTNQiPiRgDQT8mamXKYEAJ5toLSOnqReoXvDuMG9BeQZXo9Keyh4BSVQefgfJYsbqtBbRgDm6Hz0+fGmqiK21HM0gW4RrrEINzEuVn4ZA3RP16Ru5iJynxn2RrGiYVedmHGXNUVXDDAXse9UhMWzrhw9S/O2B9t2tu/bOb0sBVXvgh1pAHLdrzM0FKWSjnlGs7EMpRpa2PH8pJtKmBGUK51uqIcloF4lTh2+eR8fo3pI9ZNCTc2OXYsOgE/7EpEg9VkEDmpyuezqrBCIY9PyWwsvJpzvGMCsrV69ccd8w4KObNw0SdLn0jUKy2Ua51cZBOn36Z198YdnN+FpNfkvD1x3o1fXJAsGQev7i+dvJJqITEukunjbKb9IT5W1c8Hb289MuNMuGPj6WeZBKwFEvwS+YzpV8nJL/ZfGNmCCwYJ1oI19IsEpRJuKGq6BYL02BKOWivhh+TGBdQuNjL1TBnyRqkSuac/T+/sF9U8k5CxdWHj1h0Vogb/rZxntPnh4+PnxqQbO60L1amv5KSKbCfmNeEPZxWxvLxXRgDKTVw05xTmsCesw8QHSyNriRjqrVBLf3/Fdent9J/SmqBqYAwk7nHglq1ASJMdkEs03ZpwYg1L9PNZkC0olUOt+K58ysiPwwVM0o2z7o6SGTwenzCgkzr3Rx85LkVq0JDQFDIhpjv723Izu67n99dbec2cAHgncPDg7s479+cQO+FINS8wp0+wXXW+a67mCeZ0+eeoMGQC1ODdGoyjBivs8aywUnTQiSyqXIyq4cs/dedWyrZQB2nbBTvCjRsmi7hNnTZ/QYUOYcPn3y1KD53HnJ7dG3plI0f0ZW8uUoo/vxfljgMsvYnb6zjpYOlvqmAJExCvj8889+9Y//SCV4IYgKNRNG70QLlvcLSK4o03gabWe6QLts5fSWz+sNSi89Z15LFA6Fufdmc5lJbeotxDlt6QIAlBR3pmOiAo5G2Dh90YZfhuMgFvwkxU4uYITWdZe21qAuSRjx97ufbKmvUSyfu0xjOkTmmpA2IxBJUAHmLjM2CJHw+sCkP4UpWJ2RtRUL376x89NBdsXMkZoEs7HvhIEjqLAFgcmSCMd1VM1U6JdHI7v9oRXaCFjvd3CdLgmUGg+DysahQHCUE8p3GHC4OHkIkEuxmqjoiSXrxVRiwPfH6xhne2IggNMQQQqTCu3588hK3A9lqpktkre8u7dlK8mRw7wU5Pb6y+fOMuv0YmmYpgUIPebtX9kBmfUdIkiorSMTHm29+8vXqCT3e3Y/AEFyAzSui3Ua9Ec2K/NvsDgoFx0K0TG8dEkrMWUJMkQwvNBlZsK6npKDrLciqVAJ0Qm2jQvyf0Wrzp29yIgurgXv0UJZTovNL1Dw1fGH07IKz5j3DTBFVbW0BZiAmGa6dn8keKFwpeexX+4ACO5x9agB3+jNykfXr339hy8dbWNuRbW5/os9nXdpBbt+3c6Puzt//M4xYicfvhOZym2PCiY9XggkaYPbQnsDda3UWvYL4xpMGN6Ow+8VlncZBZAKHazk842rV/hEKOxgyXaMu9h+5QWGwE02vEMvkvU5lvjoHR7Dc8EsDc/GRochbRTxLOkb4mCiNcN58v0sRY2h37+3+X1WdwaLJdiN8OJNjg/Rm0fTxmJd3IdsMt5nyKxMPNbNR5g6BCYifjdJn2GuyiLZ+UIgNj5iyLgFY2WJvmwomdWHbANXVV8YyAoO7BOGq5vDMlpseKNOPaxuV63CHjoxHZlBl12jxtu0v6qtfMNeu2M7EKTVXuiPDzN95lzX0mYIH95xTjHonLMkZskLkQ2Rtsx5b1N1OPZvwaIlby8/vH+uw7HHhLUYtN0IXuQ24KTVEOzzZ9hvTvPgqh+JNSG0hPPjGLiXWl0jfHS8tOlQnyGP9UDWYc+yqmTg0vmJSaxYwu/meA4SkEx3AL/MWZBiX8jO61Udv3s8/Kk7HVvwTkeanxBhmKXMzUTeW3FfLYbI7zJtzMT1q9cbwqqDV9a5HK9pdC6lEUWtFbO+dv3aN7fv1Ki2eAci5W/JAGPxRmUcn8SgT7ssv3jf3n5JQn1Ia4yI7odVo3CXOH5+d3/vxo0blpF8fOPald19mcJ2hfndl3/ocEVv7lzeOnFHioVrJi8tWQY0Y6BvmgF+tgfUdT+RG2wRY0gSB4Y0GDZQntzO3XAjx5Wyei2n360h4RiJMafdGfuFbolyxOVZ1pS5AjSARrYkuFJL3cLimVA5j9rtbJlhqeICEfgFI6/ojjV4oqLV0xfzZXv7O8M/7YAPLhHancGiP6oBkYkksYHDDzpe+4QGhug462V+nVzKrLBX+Zlz20Ef0Tr6l0dhpsX+N8a7BwePiAVuAYnpJsHW+kS6dUd1dHqD3fxRhO03EAQC8GA30K7wVaIXjI5X9686hKXNOdPp+MzaiN+Ze75EMwUf0uagXvo63PEtJOZTDSOtvYosPQQEDIegLDHK0uqFTHi8TFVURODEs3xOUsFQLnzuiWugRi5sqqHIqCQnKrd+0bvMTK+YE27SVZBQ9gRYy3XNAl65ekW3FvHV5dCGN7pH6UkldHBpdE1y6zYvWDbUVGBNBmJtluXV7MSx47injWFfEy9FL7MU7YzdUmZCYAgqAPbzL374F3/25/aOt1uKruPShhAImM2EPv/k46sN26njjn2gZoI22bGvNY43j32ye0q970JI7/mEdriDKKcvasK7v8CJ6nNzYQNp9IQEIt4S2EFM745tqQauTcqFmI1feZbvjMeV97oa/VFD/BdOLrm16erlQyh94jHWTecbZCqqvelntAKHIl2zWVJc5DMSbrLQdK81Klrp7sC6cDc0oOeu107bcuLcyyP7t9lO/MOF8xeJBnopzrqomwNtrloVfmrVKQTOFnaGdD7l8Zk2uViAgcdQ7XjVuVvJovoByq73BBGsMG7x5NQTFYfRUQqDdNLLfYxDhyDEkaEzxPVdQ7eoOq1kDEJ9WnSPMMTAFjOFqBdHB/pGMlHEEEjYet7oLQXMzbecaH2dAVA/lLTm7AUpHlKw1HVCogh10k5M9s/P/HLdxWLmMo7CPtKD4wdAte0KtM4fshcOB0mwB6cMV05t2CFvYak/9jR8HY9P1E2NIs5gTh69Dn24ZO3WO9qUisvZ+eijjy5vXb539zsnWfzhq68MqPjPyPix01pNG+/uqs1EIrkyOhklP7+3t08TCi2Jc3ABZ6NCjRXGNgVtiE3nwhX1TsAfAR3TDjvsHmQBuqhqVB9quz/SNGKQMCsxT0Zboss8T0zxsT6mDmER/EWhsqBmsRasPUBmNahebYgIKJB7ShnVYtUSDR44q0f5YXOj8g8Gr1aMR3w1WCYr34EQp2pLbrnbCzC9OHD4itK8DpYDR7fsyby6urVdWgTEzm0bmg/Hndi3t6UekC53NFAZ5iGqRYOqnpuLyYQiwcLOnsRog5z2jEGg/JDEI66rBfczFiMEyooDSkez2Z5sezVToSUOHgWnpfk1khgoEaa2l2dWKr55Y0025d/f2xGi1Fm1LHN1zRgGro4CQ20jo8xd6W4tnTOJnhUowckWOxKbA1UES6X2IQHowBYvhutcmcBHQNQYdodGZIoApoUsT38rPjO+JRQCjYCmV8ZjT+ydJT2xp2L8IKcNrvUsS08ozaRZUlZAcwQ435AXaqb4zJPDp4RIso495B2G8tDyxk5peHHvwaMvv7llWAwwtsC4lJuag8B3SIwo/gpHghytnzl11mAST4Av8VzUjyYQyPk0RNY9uZ4wPcAaJ4+oYpVumRIsdPd1kexFS9m7zL+28kQWxUgus3GInXLZqHXkWrGUkj61qji/C+7kY2KxSU5yWS1+IXhmQC3xOOIjcI3US7iVMAF9qN6fYODf37h51Us+SgZ8uXERYsSk+r6XGJd1AtGi/i3m8QWmygTKDUUjHuSzqnPTVRLkGgA6tO7OZ4RjacRK5fGA62Kru/G0z1IumrBqNDWVS4voN1PV00xmcq6wUKDkAuw8fm6qsYkXzcGYZCuh/r6Bq7dUE/Sacn9Yo1pTyKYd1w1RdDvCFYoZnZqipRKiKUuOcMQo0bAMXPnYTsFiDY2nCZx1zJ5t7l007leJ1ZXDgAg7lPE7OOfbxBWXq1AYDx7Zz557/uyp5EQCwIBraIGZLDus5duv/kg+jXaboqqDNz5Alq40xHLxZAg9EZCKwsUyMmYXaI2u4M378xLLEer+/Ud33t2T7G2BYJQc6KLE/Cc9t+4+/Jf/4gxNs8PfKLLqC6ciLE4Ti4TGAE523a3b96Z5ablrF8+f//xjvcyly5sbaPfrP/zx8bPDITWGkk0tRXK18ASGEORofkbgIKT3iU9s10T0hkNNkBkDoRy9ou8tCVIT6686oCxMTALDI+VQT7+0VIIhFUyIgl7pImVblzbtkHl170qb0jVV2XsLPFU2Qg/hERBaVit5adxMFaXM84lnI4iqHi6md6luQw42qK/jssekdusXxvGBX8CQqueHT2cMsCHkV1WUZgxHoNfDOC6pPtpHlEa6AOgpKrmiAwYS9cYfxJQu8ovdRNWWyHROeM1oEdPOXzxviKU8dsgUsN5SHs6ZdfsIvd7a2jD9DZYK8wZT+fQabD5RpMAri27qX5bBG1LI5Nc3DkGeHb66dOlPM/Sdlm3MymIJKSKXrkCFLgQeMZs3O3WmZojI91U/OAdTv2KVAgvF/EmBDU70CboVhgBpzoBQmSSQ22f766//8AcLJ2TaCVO+O6eDLYUq5ickNqKkra2q07bj6BAKX0jOqxdvjJDEm1oC/qZNV8J41eq3E+nBK9+bHSVFK+vffHvHDuEbG5tEECTCIDogHBlhPi6yRn6J1M0r+7//8o+Osrqxf/WzTz+RJ+PQT+EqtYiRP3ry9JEjwHov6sJ3MayQZH3cAQPmIkskGHkSydcTyTaBDtHmayFCm9OMz1UVSQwiDvx+6aiIjZmyLJv/7vja/0BEOf1N4K7ubW/vbW9SUZ3m9Ws3aMeZdWsk5XnHHh8gYEmel039KbyeT0sJZS1+X5+m0+a4NzBMk274mzGT9fX82SH5Pr9hYXmDMK48Ztrrdmdb3LRdg0JiQullsJ05Q7zsjC3fWCye5X7y5BkTW6rf8YpduwFmDvN5cwgMkBOOtxkA+7ZlmiQ1njpllZb9cakZRIGhUUjAWdzm3OuzMgzokKoIB2KzMR1+5nxOwu3oVUlc0IsP8z+MfJi5uMO5wjH9vKEn6yBgYh2FULoBAKNsn3uv2duQjaBghOHRowNvSVbVBTx6ZNAvM+bcwcHTMsw3N8BVzYlZ+Pt0o09f0L2rLsk6NciwCXvqDWZs1tplcuRdjyjDRal2G5cEQ6m+rsPMGUP3euUtcefUPXj46NtbdzQjtVv5vAa0sw1cjeV1nT11Mh0cWRDHf+VoeGOwrKjOBX1BBcGvv7t188ZNBOfS0CFuVrI1MtA0NYh8u7a3++nVa//FP/uXn3/y8TmbP8NitiI0gm8+j30itQvK4xgldtmdZCvOZSECgtVHcbXz/63eVTmJxMDaqR+JxyERJYCcwA7ZIguoFJhiwdc4JJVLuH1ghoL4BMIff/rRpFUXeem1qckr3s0QuFjpnKJnT19KOdm7sl2dSylZKs6J65QN9XnV58TnckX4vJqx8mV6AxNAsnF1C0+f2tzl2G4IXnJQrKkx2ydPi9k/xy3bVMkoU1Ra3FaeBFgph6i8pTuUxAmqzzs1vnAkCZb6j824DkHcpWZ0yc4L+gSpTt4lUCNnUYCeeJGgSNNHJd+CTmzh7Vv9br3l0HEhK/B8HUJAQiXRmTVN0J0CeuG8YYATElCSTLORErFkE0Vd7lZb0UimsnTztRUVDLKe6d0HOVNNqMkdVFutqTGm5bTrON2LvMQP1esQEoMgVG4pWvwCF1skbb8JcgmeKZCJZCwvbm3+4XfWYeqAzpw6eKZ1/d6T508fPHzIuJhlZz1zPWzBaN+N/OmRoJQu+vA7MhmthBmnwZ2cxgzMqOWwU/DzaOXLP371L//5Pz9+7WDc0sVAPO6qiltgGMR+b13c2Nm8YEUOE9irA7tHRNAYhigs5CUpAjHz1nQL7kYIGGt7GUxQjihFUWBPD1xHnRrKafB7oVTffcJq/jAeqd/3vbo2MCfr2DRK8h1Muq/TO9tiXVtssZ66HrBHtPCkkrGCjZ7NnsNMDQNBVIMWynIwKMl2W5oOTL0YSKg630/sseY4Ibgivo6qjuV76dhxd16+tkVXC2U6BCn1oglGWbLxtPHk8SFhCekFbQgjy4qTyZ+R4NOnz1MSN2CCUYKGgDFJcWaNpTQXJry4LrfHK84mTcJgN5pJNxQzrBQvtrVo3rtllqe3EFS6K48t/KPjCfZeXHCZjqXmHPaFvPRLvrFpb4VJi7Ey8nsH7wzZzp6VYBclLFpALDyFhAkNV8rjwjCn+zUUaxXO+Vl+fMWUqFrbvoyDkIH0tbVW+gQ5wzyThTiViqnrTkv77//f/+75b79kdvlg3uMAmHXpsY1oze3lDzC1CZXha5ZXFcl7zZlIBgFgjbnaTWWWA2hVujAsNMaQ5G+srn5767a0VqdUkWJcs7bH3QROlpr/aOEFc00Wo2Fw4pt7MPeDpQi3B4tQRrihgPtGAJGgJubf0htO3SLByYLR//ccijI+KV11dA3NFDwNR2Of+RVgvTWKUeE+vaZsvyoVDILeY+9qx1b6HhCmqTwPzoUPe8OiyxH4HgyMOC+5vU1NGnhM1YlaOPrmvcCqO1pjiOwIwhJBl3ch3m9Cm3bZW4obTSVKUZl3iUisGY20xQj90TmYWMAcCRHmMc3QPTvsJPbTpy/xmjjimrxw9rwFmfkJKXhoTjxH4ubpN0dvG4sN1uBRxJkDCgDS792dTTcJrwBKwLkXN8fV8zg7lGMyRMyQJSNhmqCk7lMaDXuFwqBDrbf/7NCwb30fP6N3w7GNvksZYHQWyxLVx055PJRbGmJi5Cv00OMp4Y+fmhMRNuVbZCk5HkD9ilPGqM6A/MO3twoBBl6CQdElJ0OeFQYGqupDDZg4iW0CZ9HPKVHZIH3tvv5xRlMaonLqDOms8wgclSldyIT0y+9u32nRpXEBsJADCCNG2shbIFZG7rs7O2wNGmadIAj7kr3qaaSwIn0jgXl/fqejsJp6mgUzztF876g+liy/h+KKhnOPokmo+qeTtJY2CUZHgh7Rpj7v+D4FTyoarNRtw7Qjy+XslMrtGXObBMKTlPCUxgkaO93ZrxI5nd6epARKHFlh400wUw8yvbDck9SgNxcRiIlApcyof/qMtZcMp/Pf33FjGWMz+hRyFDgqKmyde68PUQw9V6UuT4vqQ4+z9LCcV1MQwq9lw2uQv0R/8MwdZVLD9Jn1NbRdN3lHhTwAMbFRzxC/FgAJ1aHMdL2BTXhAkbAjcCIWsvMr1CM9UrrURAakrVxM075h3dyTpM1dDoXgCCHIGcEbWTspD1NkT7E8mzbqevPeAmibUyVpoY7O/tKlvk6TpWO4s8AZ3AMVoDTqAyGeHlWHQhOevdWHFf7LP//5b37/JYEA/fw46VAv+E4LzZI1yw/Ii0abwryCCujKsuQfYgU6Ohl11IZSiG4ZOKFpwGEM8dALBZYBw7tvvvn6B5/c1D0b/CO7AVeRo/GO0ElPUVKXOAxAESQEOIARJlKSSdpJNAc3FY6oRfwWi8WBEYRBLB71vZu9HcGGFfCuslEEUCXmzSKLEDPkhSApUtLfQCMaaV03l1T2XrbNGKHKOrXp4PDFVQOtE+tS6SkUHO0AXus8QKfFvXgle0etKAJorOaIMijjHgZh1AqRWunXvKkRrZfXtaUbFZ5w7MgFjPT6eDiVDJBpzjvDOQVpMWtXjaCppqltbPax441HmcWdbGt1MfviQSZ5+rdga2vIfEHY85zy2Bs/xClydFoM9A0ZAoayDKDBq1aAgVzaM/7rxWlz6BEy38toJAwitutD6+9sWMa04zVa24Dy+I3CFnB2/LbmCRMPjZ4YzIhdCnEQGmEAQiJMYR323s6WfZCGZulXzY0hAI1GR/i4N0CLQKAAo6s0Vu/6Tkaqndd0aEJp9mcohQwNvvjR5zxMeVBKLx+6onWqJb8a4i/kcr19c89GxVZ+W+xxdOS49NU5m7j5/zevbQ2qEZhw51I2cBsnFHKwnekIUvQ+/u7OLQr0/s1ZW3DjJuoRPeRhk07sCQN9ceMiK2iEL+YE7jERgCct1jE34yjqE0kXbsXhUB1ON5tkLAsCZfRjCYOiUBxSYTBKiGR5ufv1Jckr3rlWZCgIYP6c0Xb+D0qSflAhM4uonRQ9YFYFsg6ePLHMpgBf1G8pwmIY8BIr3EHNi5sXNq1yzCEuApOMdhKzcCHvB9YRYIQVtqMn863q5qMWy05pDhXkYTT8osDwDGQMDvdq6K2+nFw0mQqIYzJLJRX2URIKteKIFuFCm0SWOxBxOLa9fLTy4MEjwx+GjcAl00eNy/U/enIXgmWGm6RHUVX5j9xeFNtxR9RbHcQLqFWaCObfDlDBiHyBHSxZZV2lofzzF4cXL5zbvOyIwecDfAz1jjoNrP07sPfm0RuRAP324UGbD8jWMtxJJ02AZGQjNPIuhKz2yIA+4Bk2aBaa0b/YEXiAzlecLq4jdpTGZEZre+vSj37w2V89/Ts4AlQ1xPTtO2kxLxYJOSNn5dRZeYoZ+A8feERCmroN74oxjOwZjdftwEFwokbhqXaClHdHeIjAsfRedYoAOYREYJdegVkJ3XHvKg0bfb9+BxdVFkkaLVSRj10spay2hlrJhioZdS3zNHZtimD5xgVn7/Ao3t158NiqN12LGmqDkfc/3DJZC6k0MGK0TExmHqeRPDxkIpheE+ullvgClGjRvZDy9fDVyzsPHvH4L5zrkBWv8wYJh4Bzs3S0G5fmA/yggONYVtcBlE64jJFTIViSG58gHMENHppA4BhER591k73sfcXo6VD8BChN9drUPeud6ppNPzFdqABlz73O0MPPaYU+7WhkF165ku/fixoxj3oqcPSJNlJ04owCzV+3EYHZ0rcGu1qnCGw2L4s9K9Rryf/OJdfTwS24DTaxMYj7G/T9BTsR53E/enhw4eK5geeNxwwEyQMnJlF8o07vor9kJNc2RnITGCYkGES1U9ds7YA61Q7dNI4KmcZgXu5DPu4CbiweVo61/vCuTORS3Efe8pZ/8Omn/9P/8lcUXmnOFKdlnCJXjVLcNyPuXcTJRCqEa4o4hPPow4vyZ9M0UCUrjG7OD6dWshYitxeJM1yk2ZqjlHlqg5mxrlEbsyh2fiqoU4rV9MOTBnZrDTF7MGKkDO9YRoZYIVu2J51PRP/ytu3NRCEceqllqvm6sMqrM2dvOdfEUWbxcwgyf9WWrzb+w5CobgvcHECUjRqKzbRPjPE1wRr5V9q7Xp373oqUj54+2X+5Q9/QWbdogcXPv/hCLTohdjdSqhRrG4HALSagHACqpLoSEY9Ovuq459H8npspSS4HCTRvZdo/btKe8lsLDZtBQ30KgvSyrJEzZRH2bt+UzuwhJ3wzaeHytzmugDDS0NfXZ9nHFocYsKNVafJk1DpPkHgnIAfKgXdFdhpZoSRMuPkSHEUwTduMSDlKheJYjiA43SAa81WUOvQTWQfZkAn87Ljwzt7eNntv0InXVsfTWPXoVE3TCpWqn9UnMeTBcN9WNLwPToE3TTYTGlWRY2t8FoFcTEe61gdh8/e0jrpaHGzYqYIuhNBkYTN0pd9a9AOWiexN3qH8a4M3aUJqUcM7iWYGyFny6o04S0vFkZtZoQBsYM/CzX+qM3zMvB2dWW/ZGnthB9Xr+/uOoGZx/vpv/tP/59/9+/v3H3z+6ccMUwaTzGjOIG1aWWrjDYp8mHt/U47aCI/m/CMx5vSMNeF2+eKlf/UX/+T6lX1rpjr+sI8ZddAeX/hw4aKu8/3xX6//PedzjC7Xt84AujFjJO8EdFAwkyaLhlzzfKQAQvOJi4WCEsE+dVDJlx7QkyeHh7/76hsz1PbskRb6Zz/6/GR98IhSUiDFtzV71o7NhthLM8YixeBWhfENzuCPthmQKa95b0EEjVGVLzljA10tSXi9u7djj3jTQPYhf/nyhQu7eLMfgo9AEnjxssaF38CDR6L15JLMckohXhKTvAZr/Y4cMLXFgSRt2XuvjfAbFdatdahGYgQwEqWS6YoPEZ9/b5xi+D72MGBZQcKiZ2TOdfe6lxAPjmpIeKpeddU335tponHAMOIg6DoaOMpQsGWGZQgUFaW5mu0G6UzRjqWxL0GLGWgfMN3nAMN6HG9ZuHMQ8vetasJHSwPC+H2+1QGDBffWbYv/4dwZSBNQdsE9r/KRCJ7+h/jTkFeHr3NHY3m+xyBTBTlFi+8QwVgP1eY/9yxLx5ixrEdSfX/82Q8+uiosd2n/yrU3L17+6Ec/enH4zEYVCPHqh69+9Y+/uXPnDjo0dcMWtB2lo2kt0V8YEfcpxzHc8CNkImA8qsGmyeSriwme3rQbwaV26eKZ1ZPk7pP1k6KkSoBFYMRqw5GrrO9ioXwlH2oMxShTvX6nHzmvWfdpsuZiV4+SkUXZmjWfd9g9j/HGkQsqwEiD7ss72zr6XHmIULDpN0eWpjm19FOD4vpAYrDNkdXOYOchKGss3hhoNoYRNkVwfSjvmExY3gUAJc0qKAiXRny5KFN3z3KXIeFEJh4FGdWb5yB5x6ZN5VQvurdqi0U4MFEmd20AylfhlOpAQE6vOE5ah4drNHDBBeUdyfkxs4RMDQULUp8W0DMhMD7yYmrMP8S7OvzwBQ9ch74phJFEghVd7YMt1aLlyw5JkUQU2RB2sozKRCCJlvzjiWtmbFxQarYmkqZ2AhqVWrJn1SVvtlRZNVRvzQ8IfiPTULg70OkIBCxi3lbOrrZKk/lQlfEDm6UrEAiy1ICKKt+rwVlV1ZHMm3fzx/C37eOhpWdg12lYLoOHczYsSfzJj37wxeefCZVytYt585kFwWaRydWre5999qlZBdNCjdUskWsE3+E1choH4GkS+Zhc9aMkXAkZWkBREW9tFUw0yXfefca5+yi7LD+aae3emuCMOWkj2rFLo1CD1egExFLf4VWR3mVGAp2GevGs1saCaIsgJMhRYXkrrejG9x+FFSNfNJMgJj4f9Lki9I3Y+rUAEVV76K9QhCMZ7OQH45pi3saj8Ig/mjJGimCI3LLwWPQ5MuzJo8f713ann8kMk3UFk91sKCoUap+flUcPHmGLwy2pqS4Ivc+sGZaVe+M3DGyWzPhxOH1gx/3xpgMww39YrxgIWBv3oTihyfYq9pAJoD/xsNGzOe+LdfE85PJBElPCO1QJGBzJ6pyQsVoXgmhlaWnuMDpJgTtSRqhMAyg3wkcfkq/iY9Dp95AnVwdcZEC7b49SBsYVItEtClZV7/g9oYIUZFRS37r+/IllA0xqRkMe0QfJsB3w3HzA21f2Xzr/vqMSeI/u625lFrExwd1P6EeT9iMk/UkGDfJHSy4gYg1wKYYlbm0mjXMwswgUlQOwDJePb37069/93mpE8zkA5HCqvGH3Au4JZTLxa3bpOj66iBoTrysSZ4URxdJPd3JMn+QL+cG67kBNwGU784dAAw39hoqQKXLEiJGsNDcaZ6gUnfuxYKi2yHqhpT4ndBy5/76rPOHEKGlE91FXjrWLtHdqanlR0lMD+ve575XkT21Aln3J8tm47vTZrToCHW5VJXBj6BZdTIGFcSiDMashIuNzbs5GAK3cIVYG92lWZjuFHUkCthULF85e2Li2aJ0kFVXXrSebixilomc3Gyb6xyh6qbZPMA6UBdpIpUSMiVXV0xagAlIrTQvmb7qrs0khwQ+7CHHc1GkE7KfbblVwPmE19PK7gUox/ko5rey01JGus27gVf+rty/1eGSc6X3+ygHmZeNZIoeqLaY/IxYkryzfPa89ADIIwEWLPlodE1PrMaTbgjZlvglZmrYS3DA7/r4d+e3/pEs0YmkOgQ60qnG0mvgiyGAXgkv0YOoe+tWMBmvV1fwjjXZ3/Muf/8SATUglSLB+6bUS6fUru3sQv3v3/rW9vUHYG7ozcrwQLmIlBCMuCbtr8aFuJrg6sjPbNsK/dZe3SozE8tGAQGBE2lbP4G+eq3dpXl6v1QXRGU3iigYyecQmbw8G8PuTRCeooaSkAkVbUaCXkXBw7s3qCqA+dRLTvahmCaWf1Bz5k07/tRit4TLXUWvlmDvB1Hg2+pw5VIM2ToQ5ukcKRcmBv0JAfCkbImC/aqAsxn3S24RD2A2K9Ve92PdqIKaLKCz1j0VTMkumaT/jLNG+5FvRXole+D4jTt/DcYCeB66qJMiZN7WekIyiVFQZd3SHH8rF92ZQzJ/lrQWqiKKN45XHB8/kEzieme16/OQZslh0FK0LPlp1zVsRLbDi2S5Y1pFZnfdaD+Ym55efdvYMYxci3uAhfHBwBh3FEXCNE3hSFdzaOCwCJ9yr63auayX+mfJh3ST6TlU1Uv/u22+/ufWd+mmfLgQ5WBA1Na8G9HDwdhRePDB99lQbCP65uXx4rN98+23R1bFxMG3ahbM9E9WiKMK1Rj7f3bn9T/78ZwYJOQK6U2pprABz5FXc1PLCfmKtE4g7mqEyJaue/vj6tX/85W8eHx7evnfvkom2lQ9nV87aSzpIdFpIaKctGm09xOy1hNkLMwI02ZzpMzXSoWFRfAvIYiajAsP5EEo4/GGgqJuyCKmCyDkE0RTo42gcJz7HzS+OckWoKIQMa9i8lHdzEVGVCZiAJ4FJQ6Yzb0xSialfNfO6itOtVA56ow9uYXVvjYCGXu8kvjFVFx8u+uCGTonclHQNHTeSb8VqKcw9Dh9UmqbVWVisuwEdxaaVBfca7hNi71cdymS3ulaZuL+AftJcNVuftRjj4em8NRVOtcFcgKvDsgL0w3GbDbfeYB4X3bARmwXBL8XGuRmCgRrimJlpNsSaaNIFZ9wRWQowpFowApqeQRzrhF9QJWTxJpxV61kL6r++dfuh9P71NhW3roD3ePD48cwZC4k225tNrMokonebLKobiWS1l4OkF0oAoKnaDEIEi8VuHh8/ff7i9r37EiZQg9uD2UMrFfL239rKdn9v7/6Dh3apPiUdVX4x9ZPEdcIJjdRaEXn80gOubxgJllYUP9R/tPLxzZuffHLzq2+/own7UjLXtoBlJ1KsVwgNBC2tc3v12j4db+ECDbRGYWZuwB7uEu3GmNhv2gkOSkCiQawvEcEnW0rWu4g/2F3ktHPphqq+Kgpzxp1oYKfde5yOE5gRfgQ79asCxGK0mhFYyNuAm3dY0QAjeB5kod1FercF9lCQXdBxd5jaxGEBVn3BInbZcp+AicdeMeSVdO3SptzOC6zmqgdbWhS0Jzeiilfm05tqpbKVq/TAXp3oMBXMvQXVaGhrjpnHkAii9u5XMyiCZXmhmt0eXRzuhdBS8dIBzwsrTwVn1069fvUcu/nuwr66+nPijtSguHM6RtDMW0KfcUM0YFEeBTxRJpU8IUhfB6NIr/VscM/GSgBrXAAaaC2S6Yi//k//MFE+RSxWFoDZqt7cD6MGwY8MiuawQxgTIkmLaW+JXu/eFBGpy2yrokkkyLam9qCL1X5HXR7XV998++PPPnt/oZXfS2/AkdMXiRep9ua1q7/9w5fmYc5eluQn2E4c4NbLA3SI9I3e528M/RBVC9SRFkqF/9mPv/jDH78WFbbXgNSVK3u7Yk3A1ZmilgUMDlIwh/f42VPUgwDIQBcQi7UbBYj/C7ubIRb7mpZmlN4QfOjpFqhGgsJ81AJK+QDgQXqfmDPFRBQk3MeMLPGJvqEny6fsBPun6IJeuMKSVCmbBR4wId77/Z8K8M/C/N3dbemnSzwHuaCBEwcHz+zWd7JDxLwADzuqI5Go0eGLl873hqLJRj0kOyry2IBh+DQthFEXtUmYs3xQBQ9exvsZxEeUisScynknxerWAiUBzd8gnHhU2UWhshoMM1vrHTUOGf2Kj0tDikokgZc7oDJjkFQnzavWvujT5aeIizx/9gqnRErct0eo1qUVOlf38cETBMnnyab0GRr4FZcKi9cxFpMMwQWwIE7Ed/f28ZkwLKkiZo1F8EiHXTwcVkFMqSUcOUiLaSTlxiWgUzPjLyGIMpAqDas4K1OuRFK7iMtCB4/v3r1nU5IXr14vm/WDMTpaFNpGAUc3rl8Hj77ITEBgz4BWwO77EdlCuLZTP/Ximczh81ZWcQpjExWU97tyZG8M65hkut+6e+/x4bNbDx/rfQyinr/U77GVAt689PRY8OTM6mmtxME+caQnOE8rRp5ZYvzmM3oX9IOGNxKLJVIR/eb2DMePj94ogiToGmoqOmEDe7PW9oDLo+o5Xj189qJGxBqll13IF1R4cRv8JqnNKgbbvDQtjWqoNw3RIZgHoNmmgTYunX/55FAf/e7924sipG/erTmWb0CbRiMyQYEZU0loTOhgqinhtGzt9MsXTUtFgJGN/vj0NW/YfWigW1jrJlF52BqDE/r+EguXPZ4PMmoO5LrsursRuOyCGoN+OMBcGvjWkoJTpIaXCo42LmDs6WfPpL61wo5ReZvVyigwYYCRkPf0TQMDjpMB4KsXwsHLThwSMd9fmqVLXuydmOGi67gfORsyYHXPvv8MU45VgrVsPxlQmFY8efYEAdg1tMVP81neaMj57v3rDtOoToThb48lKf6Wqk/utWKa9RYtaV+joVzkXDu20sgGZ2zR0QUbLr4u0wwF27UtD0aYbmf7siPAf/DJxwQDoABYpEGNSSecSKeIGBDzIrxUW/0DvCQNG5c6ANTJ6M/fvJLy8K1TrlpgndGPDWlAFPHBqXyNEz4MK+cmfGCNWrFM/UWF4Z3w+eLuDL7FgjidiACmhZ1BEapViPK1kjCEN3+U8hKOkQ73VeM8v4vlQjM237MEMDY8e2eWAClNt4XuwsTaOPmvxqXFhblLz2PgSG5sE8WKCP8JPbWNwvRPhFiraTevfUyKbf3y4RHxzFkZDR6YClBPBTQ5n0Es8z/fBpBoHF4L49WX31d5AAUm6+3Z8vryRGHQ6tkLXynR+6g4/2Z4yg7ol70ymrY03W+iAxKcsqfqgAT+OW3WPCv0zuBO9st6BjXW85oh2SzR2n2vRrq56enA4IkRznDEVR/So6pEVnOVCe4epU4dB2P/oTGRa010ynASUN5Yu1AanU6hM6K5vERDd8RlWiZ/Q5qS+oPM8EViFucdT6guaOX0alN1tBRofFfTkByUvf19LiKPSmzY4LhoH+1xNu6lC1f3d+/csxTun4jSWt5A3kS4mR2YpAj9z3lPqlo+cvYcKfXohEuDudHG7776eubZ6k/ptxcqMBZBz54HhHvdWxQ6AZmv3YJkT6MrTZmzcJymiUzp9BjASiUlKUrdO+hUEJhDT6U84kdOq0HcTltE0+ORn1pXmvEQs2sm9RwzM++b8UWk9eYy7ZI5WA0cIy4qalQ6sGuIIeDF2pvx4YMDvfCrF5LBRyRnakUMbnfvMoO64MFo6fxV632DS2f1rR9J/XPUcYl+5y61ty7YYJYMDTRDHtADbGzAYF3zCzAhC5R+5km4L2/6Hg1Dtp4hb0HKCg87HBXRRp2J95gA9Sc7/nvS/z6+Lq0vbbkz73lNHR/4cr67w9NRSXZlkuG0MjY4/Zv7A466qjIJ876rRc00YoKgSLMVSNF+BhLHK/ZYkTZSAHeCpGDE9ufPXphYG11qhMcfK/UhU9yueKoeZBiHVCuDr7HGEo1n+KtIzA0WaOJTffrxzf3t3V/95jdmAvilkFeJUFRkjzAd00FnufTXr1//67/5hZ6ba2DxUwYlRLSV+tYNaaZB+urqbK7mJK8OM0FuFQEIoHvbl7mnEA2+bqqfgkdpN+gNQo11j3P+Rb55E9z1jF6aCDQaGmB7W0+CkXrrPP9Z39Mr4OhfCFSLGmoPX6ZNgCZX2vGx0sqmQ3lHw8GT8rYnEZFYJ4Xjoc17a3iAdlZ/I3GJOovSpJnL26mX1txXP01Abt1Ne+iaEjKjUh54p4FIJtX/sWd6W+0hN5WTqsnd3tq+tHXZ24ng/u72gP6/wmJEK6iTm5GpRCu00FHhQcG4eGFHxZLKoluJ9RQAHsRRp/McAAsM76YYQw6FFdC63xm4zOSMKaOcf5roYSD2AsU4CdCN1kXSobu/GUTwLi8U35wVgo2XUGHxIRbe4LIqpydxMUgQcfXbfTb/bcSwIlwT0VmM4aRAWSpKXee5c5fOb5I0CaRm5ZlgOENNYURGFG/mrB5LcFZD99FrwHpvXzq53Dd+9Pn+7t7nn31qFX6zlkdHv/3y97PhBcl92/r91MaerCQ9zE8dn7LJpCNxLJ86f0YWJx/E6e5De9BHFvSnvTk868ZGFkjSFRKAlABXEmwWalinePBUFhogjeujVdTvORmunhF+t1p6QtAxrWdGTJMvpUHQwKeOL6uQXL4vcV1IJPmIRUPOOKfwCGwNEQi3sgw+KoghaqMG5FXRJGyEQEnZDhSM+2n6at6tSvG0jY3Thtcp7EwiqWJaq3aIkGkypzwKXLpkY1o28qKSUki6vQi9OWFKwvXwQAfoM6qTNiWhwCBd3W3GccR2KVSTyVYNJYzeUj6qQkubGfuBYyqEyBh/5b+XWpf+eTV2qGBEGsUxwky3TqDY7EIoF2jrF0KpJokejZp2FFrp/PP3bdOLDU8ePzSD1owhFw6vhpLsiBVechb0t69fvOJV2hMWeKbhNK7rCNRh7UBVW6Oq9Cq/f5AzXugrGOAAbleS1dnxeLfGtSMUbyjG+wdtkdQ89Rjs+jq5j5SPJDvAJQM1vzSclVwzISD789OPb3z20cc7O5ft28VT0o7Xn68em1Z7bMvlZ895RCRL3Jygl3wtP7qWGzTaEIIVs3rxys5O8BsU4D26IC4RQwOwIKhuza7D/C49EqwyKk1kVNCarb2dPSe0wcv3cIZ05MNFtAnxxZxozx6ikWf81WqeLFGwuLlk5rjo9eFT2KLsSIOezlyeO0IxWqnK/lcH6MrDMchOkEBkCkzxSYBLMSoIna1Z7hhECUpWFIyT08K5SmdqOnvTjrVEiqlBhYqrEtMI/ayRDf6ow3dYpD5BGTmOKLQplDPZA8roQjVkzKNPFXpdLVVgeUppM3+6DR3/FFGoevp6AoLyQ/Bu4xEKJT095IFW/k8lI70OIjuSVx1bRyQrXaeBJq1Z6Z346y9IbEB09uUHiUyty7EfhyfSZs1eq4QkGFBZ1nflyv7BowNbhptKs3mmrTfg6ew5zrzxqBzE0DqBJD6quTuDbhQ2VXV8qiNj5OnR0nL7+DJN1dEFxd3RY5A2nSxBEjoiuQQjYvg3PdrYlpR+4CLGBWl/9uPPv/jBJ0JAFy9emszGNmhLBo7bTOmTjz6+euUP39z+zklRsqe00zT/EG2GM2qiyXZwPnP77m0ZSvWKPB9KBqwcHBxZEEm2miEWwJIla8hR3H7seoivHAue/up3v+0FRBvCDwcpvTj90WrC73JYNbK68Kw+boQn0XQr2cE05BtFEyQ+vWZpze7lLT2XHYuF7O/cf/CLX/1m5CDoR1CSG6MqYuECYQarDZ2mr3F6EeMaCNhuYOy0U4c6LnLPirtk/gM1i1kcfSqkUYPl9DasSDzr/YTZf41gxoi1un3NTVHhu1c29T+tf5eDbbicFKo1fL1uOJRxe/32VbnNOUYDEPWc0c4of2/0UtoYZaq6T+2GC0lAvxxp/3wAe8KtLulC4HslffFncEjlfNiOzFlwRiLujQsszgE5JQxmE741Jl+eCFoorJDC7Iu/4qFmh5hP9RiP8dDVyaIVpR2aROOgXrjj+uTTrUxFAyTVZhdK3zqzvb1z7+BhTQy3dAvYqTnDEp5alDkhAt9Mm5CNIv3UivZTClBdufbRxUuXxfBLyoIOG1MnYz+osxcvtufDL3/3qycvnl853q/1Xk8Y1IUfQXJq3bmPDx4eoAraMJHjQtGEpKEXRpZqCWkPXx6aW9WDSfaO0owTKtoCcfuyVTIvX1vzN9gMcTWU2op2RaqFOjUeOeCm4rIgcp6CKrxybS092dm8tL25ZdrO/kXX969saLKdRVqnYx3t777+9vAl0+U1JMWPFGCRAzgtxMa8Iv26LrLiIVHoUxtuTrF4P9wCwQldBoSIjAtEQWFvpvDLu159f/T40WMhVOv6ezS46F11lRrMhTUFrhUrQd4d2TdO7CKZcyS7LfxbcnCJ/LOsmMno5rDmFQAgEvks7OkCiIE8/+fLgFvCS75VgCNprwB1sQDuuL/gOBoR6xh+RcnEoOMFkqTStIdY++L1qSFKqME+LodPn57Z2mLg0U5PC4e3bb7dMFIikHI+okAG5ky1MAsQlXFzzGDUG0gW2DjSiz1KhJUBIGqnglWuLAbKVTmVFrWAO8xSK5/Es4HLMLR+f6DWmr68VpSA+NAGj94/PHiMKzw6T1WaUR8nkHwqDAzyyfQ8ffoEj0DgZY5WLZmoQJjmbU7v71/7m1/8Has6iz07/VN+9jgGMi/GvIGn8cz6Ok/r8ubldC1XM3EhBC6UF1GWLhIaJwY+pBL/kaShju/azFWBMoAbtS3bSA5aNGRzY/Of/vzHn968ZmsDpoI7hGEn9JE3v7q2t7176eKlw84fiCgJxhiKk4u+apHDZuwrewKHtCTKlirgnGUulilFx6XcEr8bfgA3zoyn7W/6r41BYQRortfXNuxCeL55xs4Df/eWM8rec6AZoA0ns9sFaGHT6uqzp4c2TlX+0cMnaCTibKhFCg0KKYO5BdbXjJt24z54opZPl4PdfOv7IkLzdaBIWJZhDZgHFUUWu64QKg3wUzGxK7TB3dPZLxUmPiNOutzT4hyJ5YjnCzNrkUuS0pHEyoS/zaXP3T94JCRweWtT+ppT2Fgl4wTwc40ub2+xnQ8fPMHUvV2EDVwAR7lgy54OXr4RICD1PRHmRSNI4V6w6ca92vO0gHBZSnpp01MbPGqo0UGDeO9BQ7WK1s0VfE+zevvugwfPDp8JUdAg/hTxGvcviChbM3c0f2XFOoT3P/+5+sz+piRzlnN1SSpbX9vduSybxEnKEtQB0tYPKh/Zwpy8BhpMKfWeErNmJwix2gYZo7JZSqTd29m560ANLSNnr/cnqZgf8GisF8ZZzj+g803D9ydAXK2uCEP94ObHu9uOtmqGmMMHoLoQn5LwTtFss4Df3b37pwqbGo6e0ak/04CTghFoyK/64YcZIgttXjuWPDaAo9fsdvHKGpq4xdKzHJACNmWuLwvgqTCVHVswPocCJgS4N3t7u6p6dP8AM7FKeoLoE5OTMQvDdS0itzW25k1ddfDC6nqnHWeXWqao9iIK4Kgp7flMj9nXEVk3uq0d9/s78DMvA6dfkW4p2S0kmNpOOl5ilmxWL4kZ8iy1NMQYiRml4hzxJc+coRfW0J1X3KCThtRhzd7xUYp9OVd6atK45ryi02evhL6qZZt7DgXfNO8zUI/NczuiueteRVQ4shsFyDKLG/sy+I3uSK0fndgmdjhPYyz6hfPSdliSEcxQ93MiFMMfGMraeHPn7j0GVD1knO/WHHmGI8UzxyB0juCPymiyarz9SNCEtA/YqaOhgyXHwLv/8JFlZ+7zjoqdgw6oYTe006SzLl68fi11gKkwkqG5lDLsuZLtZCiocMYqXN31sA0DhizDCjCNaKlMowjsLwrM1JJS+D40ogFSElCEPRgBzfsiU80iFSaWXnJKnxBB52cYXxevXp3dQuhc8GJkdESnAaNw8J8msxnajfBoOW9xAB49coqMc5N0gFM0GBXo1YF6RLMZqx6LYIzPtyLmzPrm/hEmBve0tTutdKmtnEM72522FPjx46e67IePDnQjIi1vXr1xPggCnDlrE8hnlAeMglH5/OlCzlhahCQ1r7bgcMO3IE8OCkgE4lKEGnCuJgQHZe9MNvrolTIjmrxOA1U8HS2acY4q0J/mC4Cmxh0MQzgMAlEGC52oUmtRqdUzXL/g6JzF7Ii7Hk6BRZAo1gD6JwIuwPZOBJnW1DZsSKcymPxass32kMsBJg3D0Dh7vCLV79SpctU8rUfQdUX/GK1MlQ4JvMHSuH775sM333338fWrFy9uWnFC6EX5zpx24larUyzvE2jxtu2ynzx7dvHSxQyU0a/UJyCStibmjy7xDi9s2CdF3TqiQg1Gc7AHMsBSh7wuR1Scb6Lu2TO79Mi51XdIn0I+iSmvxLfKxF4XG6InAyRw/dRdjBUOxQE/LRiioEdSTrjdx3vFDfZZfXvdpCTjyYGzihpa+4mmWxsXMbGBeGKIu+NsIwnS1mNGMggtkjKNVnNW3adBTaOTIOwuuXknisdPZTbg6FPZQRzcA2rVRuwSNq35eNGW4mfPSra5+/K+LehsmCydRV+chk/J6VBMMtj4wb4eOXgzFLUa0u7Qz53/ZX4NtPZHqdLkStMj6xnIkangzr7CWBkVusw9Hir1BQX76hNRUiHkGSgbfs3tqZYbPB1dMiRiKLJcNeKkasjk50Nm+5uJXQZISgxMsInkHdxYbrZPD04+SBoE087cSm08DQbcGZH1VYHlvV4MvCGkAumzMOm0aNX7iEhsqof0kAuyxrO/YAGnxFhQmPS1P+CCa23g0FQ4vn5dItDu3Ht478FDcmFagN8q04f63L3/4M6du19/Ky3u3sxVy4V7fO2a5SJBB8FejpSmqz8Yjzr4mKnShJF4YwODYeMsEOBLH/rQIpIyUu4+eOg8Q5i9PzZMeaL/l13Hu5Ki65qBGQJg6PQMBgajBzEnoxcLwZAtH/C7k9wlnyAzxNRoRskDjdJAxS110EeljxHBooipxgsaWYR1hoasdXVX2Iin9wf2uZkwyZ8jspLJhOnmWaN4CDvIY1l+iTHhOvRWU+xMLif85bYEhLNnrlzbL0a/uuKINEYVtL5YMQz+4WOAZ6Vbt8ZTks/TyQx8bjKnp+pMgPMd3gwqMGTeGjudTDIEvgd9Ukt/vida8ZlRkqFjUAJT6YioWMgu5AIZpRotAZgiaIZGi24zcfmKJXurbVZ8oGpcVl31swisxfQVtvJ+xaMgo4BJUpOWFRvScLiEOLXZCqcmH2yk+dbG4DarFDYI9kz+ogzho14CBdT5uDOwjk7gMxVk+1LPkZtwsjkAu/Kc8/E6xYnYieT4rt5IOkYs0S3UfNykWncf3P/l737/ze0WzBi5PRH8evnKLmav3sgGfWVfatkeVo3x4X9WmLCuFkbxAB/bDkcfvrG1tfnNrVu8X8arGBEH6RS5yr9oWhEQLYSz78iFc//pl7/7+v5tfQe+chgW2Q3cgYkmeK0m5jN/plvwFIcgnKh0u/+90gV7npFcWzGN7QhEcTDICYctw8AENmvTJBapNIcllPHi1QuDjHb/jI0nAYqqU0zPWyA561QjNafPWZNj5QjrRmmRt2J+NSCx5qt8m9HFuR1c826dIWzmv4pdAFSRCf72+pTMEvbRzuz5DFWsqQ4cdlGDI52FHRf72nsBgdUQc1HtVRHfe5SARqkseOX0dQAsVgGw5WUT8wYnr4Q3pjcEZMwKmOqqmmoYyKrDxdRZWx/WPiAZXmd8o69Tx9KZh/cPuHk7e5eFy1+/emnYIHc/zvauUQRfwRLjzgm38EU7pFVC5njeG7YB39m9XO1TvF9KxPaBKEaEyPJ7ylQgY9dgabFyri3fxT4BJUfAtvZLJwxzdgYAUPRiMxBLF+dN1GWYeBazk89vf/8HbZJMFSaFHlhpLeiSe9hbbukT5B3Vh59Eq3JlF4qj4P7+3m++/NKgWWCgnaSGj/GVkA7dqVDNXby4dfjqBdMKpokbZpXtopb0j/gH8olgjACEd8gnJaCfvoWUwweg/dSH5N7Saf79gT1Dnh+eNZK0GJ/X9DZ/iQuTTUtK9DARjVP/Mud52AzYheJydCm+/apXS4IAfRzUUp9goOU2BTKolfuSaiTHI2bJnZIVH3DBmub5Bd5+UbkTRzw9//7FeatiheTUr2QSH8urGQDTpTpQjBnRX76X/4grC7xekwXA5izrOaHmzkK60bzqAbffyfXqmpwZdTgVsq+YH0lrUn7KmRECBbm+9cnB7dWI3KspVUbdFSxZF8/bssxnrLVHegnCzRDOub3HALOb95Wr+/fvPOAHWsYZzJxDKxbMJr0/enEoSLhiQs3Um3Ccmhzn8ap1nG/tjVn7dVARE1RkspZEG4cy4UMigx2EvHxpcBr3FUezh160P4fIrOZCBymjr0VwAUEf3XE3hzOr1mcwnhqViD7mrQWHoMln7zOJ/iQeEij5VASY5hW9LHC/9ITkT/Onti9dAp6hwv7ebvMJmmq9X/DGn6jfNgKr25ubHI98dN8DMNPLFJFtb426UNtMVBRIvoDh7fyfNKPGAM+pSPQIdd65q2GdUNfLN6/vPXwkXu99/YRRrkasfIqRyIappW0cbZw/2zHyq8fnOnPDrrHnBWd2t7exAUjM5P72Nnqi29QcjRAIPNbd97eaapViVQvmLEVinP9TGqwN6DNCQ4XGyrYf1HPB8MJFmaf6pDB83UGDGTB2Q8kpHD+qNL2x4OuDo4vxTYegQZQh0+IjzBUHwxANYLaeovM8ckNYOFKdi5ttMahxQIqbSHU6e/acLhPhnzw+ULU9ZtDcRt9nz9oM74PdMc7auOH8WXHbYKj5xGvMB7xCzY2kb2AoJpJJQgw2FixHTl8+LcOSDBZGb0TBGxwTQKri3ZAmEdSRYKS66YlhnoN21I5T8XpajWYRfQgfLTxOZhKkoS5gFAaBALcIobawy9I7va1iSOwNVGVtqaXNaIcLq+eM3e11kHwFCzsSF2Nlbw1ivuYhANuUDigSwsmIqVzW79hyHAf4AhQH20imGQiimOOo/Jl2tVkzgfvTH/9YTtGHVuVb45Z/Uhv1DiFp+ct5uc1yM1STILVUalH6+iGrmNMHtqninlCS/J4KR3YsPjIuGVLIAYzN4O9/BEyqHIPCS7u2u72+0oYchghnzhYCc+qVIgwa9PHBEtunz59/NEec3Lx+ldly8gQAmV4L8PiydGMUYWEPvS9cawSldxfhGTqmJOMx5/WPvkKhJ4EXD9OQYBsVmlsntLu8fQnusrsThfOWUryVJSZVxpCAKVO/nscyHa8MFVZI5+bRFmKSm/v3HlXhh2MeiOhTASv7N74sVYGJaf+odVvivW5HpuQnICmkYQzaOal0ZrMEc2zgnqnhJYJzLJ8AFPtw/unh4cbov9dG1MD/pw/UkoUsQX/KWgWAx+gjiEj6LbSwIo3SKYqJfk6tn2+VyevXQnaKmXUCFp5iKmjFLq1O8d0BK6oULhvzt5DRb/BDwK+EATPg4qLvWUIgEFtuME3Lr5sPYVCKT3Ca0RZZEOdhGBT29ESsQK4y4ogKqpphTLWl3HhUP4Hf2easM32Jkp7UrtWXbz/YT/rq7s7btzbRkHZExRsG10nUiuuVu/fuc7Eizbxv08NQWgw/+KgNF93pzQ8PDgoghkeMUtjLqpqBeNLfx5TZBOlSC/3LTL4ieBalzh12UXq4lh60SVNfjo17Og2AoSjPvEVYtNuyQaWHqg7LkU4qfHX+i89+8Mm1a5l5R2KtnbZmgAvJsphepi1RbpgAFs1TRotkS3XhOAF3HhEsy9j4izpiAwbYLPLvVZfx6kQZuuFdAXXLbZRnTE0hS/3dONI5mKE67hy7oYKAkQ0GZ8Vm7kDEnXoQ4b2+03Kns+cOX0sF60QwxENAKT0MPLBt3VeotwDGBa5s/GOrIU/UpGTalf6Mo0ku2raECPKLdnd2tUl4VYKeK+eHKYnaQB9fExRPQ8BnYAnJ7sfkDpvFWM2sndrd2wWVfRE1gfwP7z+w7Bs81kkzohcuHDlGQydmZ1i7HaLqU0elmMKkz2dOSSphnsTICNA0FgBRvpaG2H4HFnzjywhnF0AgEc2ClyLlbx1OmklIeBfZURbQS4kZOkyFXjNKiTlTeejAMUWDYNJI6UTt9BjBkEkYIzpN5zLZVPizG9fZPdVLowPWqKjDZ18aRaiXQSFOZeBBgfRKcFXzJPuhonBbkm+uUYHIFzGjbbqmUpycdX3a1b8qc7Tyls7WO6elgaG8Rw6PjSvNW4cwjlAii5o4fewi0kgb3HG+WKc/YHCToJm9xZZEytXLTlI7c2CPmYxiFTc8Utnp1ZPNx0Hifq/MW2iKWNRHTQMFRPr4zX47tQUcvgw2bi/2o4qjYTUgL5qic+8BGJnyYsvFasDHe7ZZa71oawyRVe8cfSocHSxrzOOUvoMx7thM0t5h2VrHo50zpbAuJttKaIvgZImvWRUYx1WQ8RtOcspt0VuyQDt+6iI+XNy4JELCuT88dlzVzoB9bCQSxM05BCpi4l9StUCOetk8CHqY+bRlnr2X4hEzBGYx9U29mZ3FTl29vj9WLnE0DwMPMVihYSuzm7pxAGnbhtcEOKnBolnZ6QF9wFhoABaCEEEGjHFHvZnkaNdhNmftcU0IRpZ7ZfjmDd6SRTOENQUbdo1HxHzgV8pULVOt39lyqohTyd6MiYdvakv9/MRfb652sOccnq11K/jrcuzneOvOnV/8/d//5ne/a+cO2bjPnmR97bSZhzOaa5FpvYyDhproe2cJrkqz/3VBIz7ThElxcg6aWkXoJBb+Q5BGKmEI2jg0CLjwnp7R7vMSja5e2dNPEG5KKat0ohTtt2HBV8JjwGpz4zpsimSfQ2bzoqEcGE9JP17Gqfk21IGeN30bbbTwfVtxYUi8gKdown3KMS0Xnh++pN4DYEyN4r02mPjmKsVBX7z2Vh8AIin9cVcz7kCaGtiW7vmL5zOT3wZv+AH/oV6DJwZBXPLl4Ytzq+cAOyscVm29RpHaaqjz4jsZ24vDZI2eyK++KBU6PpJ2pbmbN6wUZa0w+viTT64NZYXUSrEknRr1mRpyIKaOkwrh7umUh4ia3B+8CaVnKIfjw7TBWyOJDzJy/DpKPbscUI3Ao1K08XSpcIwv5jQGrZDS6fFSIFxA4y6YQQUXtwAzo8rJDAXy7PVZncHbSknigRp4buWv2YCSqL2f5UwxgJaNrY30QIUiprgSSOiYlrmaumAdS4MVls9fvXxwcGAxkK7VEeWPHj+x88VX334r3spp96PAvQf3yxj7sG5moM4BZqpoetU+qO+4kW+bhTt//lCSAngWhNO5E7kJY5D1wMWQDfYRIegYvZBfX72yu3t9f/f61auSwq9fuWI3VbR+1aFj776+deu7u/eLHXx4b9Uz/A0DiJOADyrrHMTyzJt/dO0qGiWf7NNQFu1sIAhihKjFKKtthDgRCwvWwCQ7yNMeZvKPRJ4tIHx+eHjm3A4+e+VPVg0qS23D8kiu0jlCqqNAWsFXPNcx8y0tMsVCNcT98MiQoEjfvDadwPG5C4kyaC9tnt/evsTE2Ahqs+T+tIiB393fTq80Tybjdn8iW3/qZ7qLdMNeNWfZQiEK+/RiRvekpw7WuRUIy4snd0J93nBRZHYBgHDUBAaJPrf+NzlbKsE4PDOZmADOR03mItF9ap7WAbzEyU4AVvmJhqH/0lwsGfpqZ2nX/WSihJ9G53wQLfaiBjQmcWg5UZfQTKK2gD+BG2cD4oVmFUc8taCm64xgEHaTHIT61F9IwMicDA9HtM4D/w9/97ccXeMfvY2QraiXNnlfQZXRf3//0eNTev4UywDF/wYedTdsn9GSARWhtEV2iwQCfEDHYu1nAHwHF73rGV2CpIOzszVzkg+wUVBS0L/8iz//4Sc3thwefc7+uecpVawVov5w+ub+FZqtRRyZLT+1OA1AhsiYwbB97Nq61DeNIrQ7mGsFjGIKwKHbQTFUGWl2lQUXektwh3ZJPBiPLB0kXkdHpsbK11c8oYqInkZK8rfQ0xO6d7qsoUbtl3e2kk6VDbLh3QZ4HDRvT9MsQq0kHe70L2pNF1EbQRgjmzlMf2i+SqJ7VqPP8nvp1aEXcUeF1c5ZWAAMvPnMG6qfF+eOYuofCR/btDS3iNpSbniGqDjljZoYIE/wrWQSnVADygr2aKPW+TpSNzRas4e1dEMFtyx0TnfTw/jh1pQfMAKfgJ4I21C4ikZqkrB8coTSGIySyAFGTcZhs9UxOjYtMGOhEJ2AFwR1K9w8/CMK1Ck3fqQ+OUDLMIC6elMVu93PjL+oD0jxgGvKneHvRYTiBOQ4CdFXnDp8zjavbF4y8SZt1frGt/oFcikjwbhQpaVxPz5gULQcfgAXW0uxQ8TqdTDr2hgYcz68Z/gz5WhT7O2U00k2HLAg2iNrQXBwWAqe9bMCkVZzH21cu7L/OMpmL1knSKcqE+6iuPBEA1D5sb/XEC4rUjG8SvPhFxm6NYKSaK2umPfpZjQfTg3d2Ztoyr8/kSFu1Vz1Z7mAVV8oXJbzPz/UUm+NhI7Uzyuq9oKW/UeZ/uJxjrp3F8hyLOc59uTyjth4pnwmw9SVm3oVuovLvTgff9FbfaqtqnDue4/dWvCdksq4NRUOUwKBeE2fMwgshf1eKhxliGt1C0ftUtVgM+qFNiD6As+aTdQ1rNHRjShi/M6cAebJk8OdnS08OIEqMzTQAqB28xAXeNOXKNQ3Nsp13VHf3WS/RWswjYnPmRHYyFqtlN3DLQBWMh3dMM7gK5EgFMBTaQ5s7fYrCtWAVRBsIDuG2209Bk2QgAFdZrqwzAZNJ88+acjRgbj2c+GBV+/tm+uO2vUEIGBpHSlW8ZUVq3Y5cNk6SBD6YVrjDgpTp6FIczFmi21Mg5vxlSz01zRZ07R0k5pEWm2GNraVGYYgZ4/PSsgWKVFbIivOYOddSj+zJJD3bh0VFCDR7r/poYIMZWzRuGaQFVbwC4Wo7n7MGC2I2CNLyqonAvpRLO7EntD2dzA5eThSOOTuodqyNUP0/OoRF69o011chEmQ9LtaDp++UJsYdJww7OnNRs/xm8JP0s+IF9U/tvU8VohWtyL0+D1nWQ3oI9CwTCWpauCbBmK4RqbzAWRNBrga/oTFfA3a/oe7vwsAVZNxKWER+lGgEKlYyZwCSDIS6+l1QiXC9AqYa4NB6jOk5DJJsprwRiTorhdUWZNYFCFy6qrCq55/j0WennALaUGcGvCSZOlZwyikaxyV+Vxb3LMcchUBL6wDSBJhRrbbPshXoyGSaCbUrmLIybXHNIMNF8oLh0I4yjtt4/jVi+bPk+KoePj82Snzbw8PHrUrplOrItn46EYtcqSljL92JHrWXYu5KOYUTB21kwDg0DoysD7aCwZ6mP0LHgQc4AMbZND2P4oQ3d5a5CtftRXdDt7WF+kKjopZjew3G6IXUxeZp0mCS7qaiDtDTCyOqyXG+iB9VhB5kuHYMFz5Xg5qbSGfq0DuxvIJ1BlmoWsPUCDwVx0B/OjhQ5egvry7CwB10m7SAlWoQWQAUBEYqkXb04qnuXaoZzs07i9SGWzJihlreqYZ8UxGH3JvJyT9nUH/Yam/1iQdb21fNs1kfzEMvH5tL5AGVmD5i5JBGSX9gELTEXWBX4GgXzqEcK0VZRKNAozcFRGw5KoikalY/vG7zorsyzBoKgw/zVQoxKN2eOvV2mP9bcvjg6KPu7V6Akov9m25SyqmYGI7hhKtxGoCQWfTH4X7qCpGkhOWDvkKlpyABBD1lfCzOA0DF3maxIdFrrw9KYZIQhsHmGqeKBrV0gYiY08ctBrVQMGucCSbBYkUa8YIp5xz/92LZ/cfPdizO58TX6LT0bMXL+7JhHjzyn52hy+eN1yWg/XqhYcBPTgvvHTf11pduhuPUT0K1Z8S29CYj2I+yzWy+njNWyyDHgloRP3UqmUxtmxY/BBa11ABQMYgtDqfjlqiaEyKAWSEYlVP3n++VaXZ3Q+dfiDfYaaZY6byQ1ANhoJi3ZuPWoNGJcOOvqmoXaJOXbmyp1r906F17HO4mIDPk4PHcHMYIY/zlbNl37+7emNPlq63a+Qo+U6vWZrDwzFOJgE/PH186KQmW6oZYMt4n0ZO6FY/Z5r/XfOAWnEyihgw8qKIYvUjQ3NAuQRnJm8MzQLzEBI6JyI1yELsPyPoUd8HZejgEJSkii/cOFFKNM2ecUvS56XB5H+xIJHGgygje9gkg9MkBANo18Dwp99VEjuyIDhStzDUj8Jg0EjzP+2h9j6/ukrTyD+psSvgmbToCWUYa64eby/wLw6H+rk/fiOFXz0efEmOf3wEH0qV9KgjMSrTO+PJ6dVR6wt6BVZB5QP1Uzdv3rB/0Vd37hF9MuL8CyeNyrgKiiDgZYxJCOrm3qeK4IRVYkcHfRnvAfr0a4S9Zmo/b8+RLWaTCpKCKcFPDbMz1juw94lO5xS2FntgdoBcibGJ+JAquS9ngUdW9qtqIZ/xKroSIPQjlRvj1DuaPZY243TKOf1Fa1Wh+IrMhQuXLtq4zNoUpABK0EQU/8iA2oYuGji1bm7uq+fPHcTEUbz73f2rN/YdUS7xhgx5g1cDlRRAg44Gc0pa5EoIhj3D5uPVze1LpbI7Bqq8mlZNBAvkazEp8ZIpHlEmd7imGMkeWUd//txF2OkGmy0ZqOa13hqRVo1BP+Dd6PkIE8lbpm8DJCFRaWj6rWS64Tqi1Xygdo/O9pYbCFfnTppBtbw7lbsccGtIze/NwdElIj0Vusm8j1cAsZEY9zNI/38WJ6eFFaYG5oU0oSLF4orq68oFSXROPO53VgkBiK+/d2XffOK3d+58+90tpPv/lfUnTXZl2YLf5x0c7nB4A0cbTUZk5svkK1apRIkyTTnXQANN9RU1oUaiyYxmlESpGiuWRFb78mWfkRGB3jvA0bk7f/91LuKVjAeOe8/dZ++1V7/Xbs/wDe/0S1U9yIQwiohLJFEvPJqDHTwkquO9gUmaR/cSa2OSMKnSaA4D+ejVnOGzuWU9N8zJhSN0CQFlWfl2sBXL2JvpSJCuSZREJ+ldgVKqpDL0CI5zCctEGPba1/vx4X2vAVNIi6ZQeObsefEKQ8OuWcSYbhoL5gvTS/Jg2YbYSNXrmDRNktq1bWFIooVWUkVYd4YRhrTqvlmntYYOgPcgwkYyevbOsXNCThSNKsSN6hpHO8h4NHy80lLdf3QMmHj44GiP+DFYXd7/1cj39raj5C3P4iPpOv8VEnJ4zYXdwB8+GAwDb3lRmhUNXkgOFJsXYTckEAZ5BYmpple02Bre28s/7Ji7u3NHJO3whWFR3gcHhoZq4D+UUWREtEgjKcfQ+gCrdnhyIq2eKEzkx6slET+Udj8w0n3CCdBQPtnji4S4UVZ/ScRzmQbnurzztEzpVo1tfKSkA5mUk9BcbmYk1GDQolajbeMHGlHAT+ss1YPnuPnLb7/+27/5BW91fHTfIN9//P3v/y//1/8aV0fa6gxUgfhK7+OeWtTMiah81KbNmN6apfnKo2drYzPaQ0ziuVAHufR5xcUGdMx2ZUHoy1cFSROmKJ8ebQCl7PX6SbLHMSyWdpc2V89wQ3mmkcEVIM9rpeUwoPuLr782wLphJzftrK+MHqAzL6iQKwZri/TNPam3LFkVfYGpYn9LKYjHZ88WLo9KjSp50PjAMiaQRRkID7eR19SXm1zQB8GF6r7mSoUnUZFE7GhoJ7beJm/HN+deUkrUbWhtbHW/2j+09uHq8uyNlTT7On+ZW7REFYttpM9sxp63qELIcIQtbPyLdm8UP7mApmamYfW4MrPHsE2G0mlDhwuFWOOwkCc+P7FkkG0RQeLKV0RZyX1XIu7AoibO5Wb52XOPErFsiEqlJUKjDbvDXuEEjvRAGZk9zUqCWAoJEF6DJQWoK1IVxBqAQPMvDEag7gnN/YI/eGE38QU4FRmhYqr+6z/9x//Z3/7q14akHj26p3HXDrS7qclKb1X8+I9+9Tc//9k3f/f73zVkOTQCRKEhqPbW7d/2Mjv/qHXHOUu/cl57wzAxSHMAmenp9UKq1DaP0Q20VWdl1/sPHPHmlhOhIaeKz6xcaYgSOKEyrREmBAWDsykd2ZU2I8e9nFXwyfsk6i2CQ2O4f75Z/ucvXuovOgRgjGqCHMXxN3ayVEFXdvT85SurZJVNzLc2DftiFlLgVS3W5Gi9iz6b/qtCxWdxgdpr0V0lFfeSqAWhFg3v7t2eBmHmWz55y84HaodJMlZ/wu6aGxC7z4Pofnmb1r3DWpKYuGm3Q48t4vAG43nLE9S0Ld6/i1kLJvDEQaD0j6Fc5LdmIuJIqiyYcdv+wbIC2ceCri/6FiVo+qw9IMkZS7sWHcuLzwVH9YAfue7L4ZpPWE2RSEhV51plmIyssbMWG6/MqxbAJgGWMGcD1wkBIfjYAG3rO9Rn9TskXr08aYvhtnnGq5cvXh6LG3kuD6La38q2QmmxjTQ+GwMBzBALTQJSQq6QFgJJ8nIPKw+sv2IVPQ3ULGqiG7e29re2/vf/5X/5uz/+MQjB6AIWdyiOFN1f32aB9QxZhLUV4nERqSr0wKJ0xjIn3DA0AHjFqRbLNlIkGrcyPSOza57eWvEzKFouHZoqYNMoEWV58Sa2jk3kn52gjHIBQK1x7UK22eNk6gNvPOAM6hvwN96TaQfGJ8dINnyBEjFYglwkDCcV4bDD6M3lHe7tkzLkBRngD+nNp7gqWlsfV9WCztx032EbhulTcpDy8FEDPpWZsuMA1o4fHqHN8o0gexSqniTCEeSwLsVEeyycuoJvZegoFg3rWAT38tP1VrTLHS0zUjF45FVb6Jb4We/IrNZNMR0mG4VFSeM7MvL+yTv6FyFUMyIKIwap4ETusADyU28Z/ffk87VCCXvlXNqKKS9PVwVgOHbOkfll6TdxOCqONnvDp9jD9ms7mx2zHkIY3dtHPzglG4Ib+1uzRXjr7FSX5q7NOvv7h07EsIMiNxATY6Z/y49qrcpV1fPD/YLA2t6du9NvLtlfSpR77b1NZoLtmqBaFMozKAPj7te//IVtn09fPee448UCGEun968lk0+AaogiUx9maj8ImZhTQqIy4oI7c5GITrkJW32BNHbt5vjwfiPxXhBowb3T36duPjvVKF6aMJzqUymxE620ar8BNyc1DY5pvzytq8sNLJMLC5KiWolieFk+vPMagXPBcwfAedtnXGuGD0FYkCLCwZGDlqhdvj28u8/aFB5f2yeNDX418LKZbko8ovUBPfwHY1QZTKQ1kXHLNFysnMLypYqN5w532gwUj2lqsFuhW476MPicjtO4jBpPi4lyH2WoJfNk5DNiGMSCgwvKVro6NdOpr5/WLPlqmYaVfJZyGX+EBHg9lSUfPIpSLZmgRDPrjoO7fCdAUiMlSSkCXdWrgmPtSIWOEh6Vo9J8DcEt0MMF01KFzzl+gkP1BB4oVIRmzDG4HXTQyCN+oHF9wy4Ir2a0qiUNu7p+8PCBISP75Ynk7uFdy3W4XqukprLE0+hJRjv4jsjyE3E95Mav5aRVE9GT2Nf1jfW80FA0t23/pPn7W7mnIap0J8H9/Ntvf3RkmFSaNiNgngLjYNO7d61i7O3Uwn+sd45kPqYjhbQZMTBT6xTAuKBNS5+1eCrmymQyaSWt4NXrcQ72X54aFZEzzUYR9owSdVS3NQ+JLj73t3z4hfa8h44yTSCV7umVZOk3uxZ1a+/qKW5rs5jsTVtBRL3ZqAsrmt3MhbYdx7oMp/p+OjLVvWVsTXinslz31OuLiWKO5iKm+V8/ndXE+MA1gQ9yGI0Jh7/7KY8zMR5mlV323and5MnIaqkkXKaInEZI+Sf5NdmCQyUDyk22Gk+XdndJibV5o5uzV6eGiSYyLhYGCTMvzt7WaFKBT59svTl7fXbPCzltdSKthGOTwC0VYY6OgTEirXyu0Wrwj5/sFMOrw+ODcWmRG13VFvOq9/P94Jyp5ln6Hio/Zy7XYttT0s+lILmfn73Vf1e/AmY7eEOGmrNIA/Om7ai05zMv3CIlhsVUPr5dnUwMng5n/E5ZqnpMNcUdZCcu6qGMsVYuuVm73nFNLvuAbTrrfVDnBClqJdziAEcvdEpFV8AifePn33z93//Lf444BbOf1cMN8zXOHP7w8T3lLkLxJI+C67lYksVqyfTEaiAK7yENhMOcr9U81ZioYyutY/t0fe/wcP27H1SYEnsW4p9Vf0VGGJfU0fZojgGREal+yL9mk9GO/t/BoU0ktsM9cIjxk0ceOLHMClBbJZzHEZ3L4gM4xiEcccT6tQ14FridXFw8/vhu99auTipesR3TjbkIXFZrdJnRCY/h72g9GKOm0T8+O00xm9g6aowNQz/pHm5GnlziHj2/lNHcShPyHMNQjo8hFUVX614SYQBK0HnnbsMyhjhhaLWsCMdokojZoLhJUZjc3vHubq38zfvLt5ZWgVCVjl3gMlOmQlVdZ70U67G9v+z1i9PFlx/eu3d2eiF03d22N6PYqVknJXllVjoba9J7mI9KDWXRjvKIam3z1Nb4gSKL0LCqFm/kl1NM3+IcvtUEoWVspurs6aeUFmkal7QBw6pLXtHIlzMmdPdZr7C2bfy3tknBmyaR77hLTYGlR9hun1nVd2WcffexoJkyNrrdFS7jNpvIs92Hvdnbii20iiY6JsK84+3GE6w4NrDmdKYZPq41RijyP90/OOTLAZF/6ip8VRs48Am+6qZVqc2IQcOhRoK2HHiEsbUGM2+PfdRORR/f2jLQnhCZWYJKP3lNBv9EykPOKNpoeWLIhqIup1hz7JsokMcy/etDtscPH/0Xf/vrLx8+8JbPQs+7e3guErC83gLfP79TSU3HiKSJhcya4q55VU8epB6qd3v+8KNTw52PklB5CSiadpiCJMFN095GsUMCTi3bAGIghNDCa7zSoL988dorDjZ3e0dL2PYXq9yIwvT7xIjspJGNwakMGJ4QR4Kz0kuiHWp4YDCOSK6uL3TCBRU4CRM7Oc2P65vpetJDR2ls765W5MUipynf2XUktTvv7LCegoYd2QVvieUnR2zs7x3sedOCiFnH4+3FBS2g+pnnB5s5D+ilXQoowoqQHktwg29c3OhVyjckYUaXPFXrl6YfigoxqdbzRNUIceiTzAFsbDx6dF/l+nCN3B/f0w+2r580qZpgyTwglT09sWb+4/7hAcfJjA0GmBY0VnN2cqonRkLDMJWOfyxilBI+Y3iwqd1esMIlmf2gl4wAIYhNvW5MXHop2QnLY3LU0fg7HAzGR1E2T0IWYlrlcMtEfI3JQASN+tm2oVVoRe3NmvhoHHwdS/pMDzW2tzfbbD2sS19UmAlhN6AeQEkoIezm6ozV2BfiPBUnJQ2/Vj6+wCGSGruNv0PfqB7PUoIMeLr8eHz84Nc//5uHxx3aequN9JMsRL59pR+yvf2yGRPyyUGlsxMicc/JFR5ya5d++/s/GmXqrJSCjzLWFEDfzJqlsVrqxdQLqFLgKQqVCIqmynANzYrYBgC4GnEansqZLGyHsVFnG5GbTa8IHc7qVlXFr9GtaKWLQjo65ThHuitUeHt6xhKaLNu85TTCmEjS1h0iSENqjOVWu4qD0rP49ujxfWbp0GYHwFJ1svcM45z+gqww1HB7K8WD486ZdQ4A0e1MGL2+8eLZS31ZDhk0kogN/WlVl0u1KQV4K7wh/Q8MG5k3FJ6LjZ6qjZeyYFGJKrZVv9OiQoNjcCoZS+QitGyysjhHs5WvStYfPNQ/LtQj/XsWOOJgyHgCK/f1ozLV7FMMUwQzxFan27KV/VpbbcG/ASzW6FElb64dXvT4+P7OjmimUfzmZ+pcFWLFtCaV2wB7VpOQkVfQszs7jx89dJjil1880jv4b/7b/05M2zwb1qsxcXp3upY2LyMmEw6ozdV4TNWqfI5LdNRAo63W293acraeTf7ISDzTHruR0QVA9zBAERK73CWbMVueoEV2pkVEk0Qtz5Ce9KSwC0NDNQqqFpBgZnmSH7BY41Mbqd8u7HDkhtWvEjyllMMpWIja33sDnpWxYEzlQ6g8ox7hFkTIZvH+iwhBGJ2McKzT7Fh+YUeyjYvkXdGwDIll+t1YYn2+oUsR3DQGaseT6fsEs3bDC7qxC/nCW3m4NenO3JxT7B3yZS+RSNeJ08HkZ7zF+ZMo4jV6nSuDJxyUt7/lae3RSUmuTXkalbLoxdwF8m2pa2Bnva15Dic1L40oJA27l9Yf6K7ETNNicITjkkozE3ftgCGQ/NyU9Ww8xmSZeoOQr6nf2es8Rq9i9QLYl35wgk5X8trYFWjGPrE9SDXnSMiJDNzYVvYwGtvo6Qrz+OHqAbbOMcODfGUg4QmROVnrlz/7mZizSQOTpI3bhJH/Vpby3pa9GeT03jvnSetAP3nEexx/+/Nvn5iDOGyq9PTiHU/6H/7uNykPW1nkSHvB0whsbFn+/On9h/aO3xhptTE9oxjuRGQLy/wkYKtlOCSamnamZhGAndrRaPA9zF2Qi++TqHj2lwbNmH3OJolMuxdGWmcNFMhnb2z3maGsqp8GaXEgsmRQxgf2KOuL16+84YvrBUGczTFrOk/Ovb/9/ODu4ZMnDwEfV7goQUIPV2RnXTEu0RXUtprN+Q8ROPE0b9Jr1zoh/dxQIEZXM2gYleNpPdaow5gxVD9+Onl1cnjvrqGFVx9PL9+/PzDCt7ujm8C1OPpKtKanwGHi8z1zMqCAh5KxbwD3SGyvkXheCg57B7t315pUGWvBdsa2fnx/P7XIPXy659jduegH27jtbABchqH/cBvkgCeCaqCG/qTKRFmTQSaBfh84kkRGG7ifSWjueYGlwhxtvsCbeWZ0bDEJSDhmwlT/Rp2cuJooc1zBBJ3fZwxXVojUtSD5EbTagBoMU51hYw/yK3w4bDQ/8RuHRkjxrakh+tDWUG7q1PDixcU+N6E3mSfNC+NzEhoIop1f/Oxnv/7Ft3/7618eWPW1t5dWGdHvVYj6dVcmo/53/8X/9u9/93sCH3pTC2zV6FJv86Mook/kUihV+wh04bGFRbix9cPzV6/5vfM3ry/O2CwWlCEnOrwc+iMOxIiJJSlQUndlKWW/sqzgzNIaryTUyAq3li56utbkyKZRapsQ6BAnOLbOKCpaJS4t6caGCWbbER1a1vjC2npdTOvDtSSZVa28oEYPz31akAJDdZCEbNecxKS+FvB09Ce/4oFsDav2/HqfWsMZBgiJTRzqIrrwDJjk+GOo79YX33yBSNxQ9YNH90aE8qw9enxchWaFt+xN60RR5GsiDACqCQRsVNmowcIAfKtXJhG0MAopzmAxObRoJ4cEX6NzuQaBl0S/gURn5SZPKKagyw9pEAZ6ZOZmGjVZRw+Hxz0fLq+4Fg5BxC7BXyZhJYixvaff/8D87h3vJ09ch8vGmgjx0pt1vKxz57Ye85vT84PjA6Vfv3ilt7B/ZP3y4ijBW/CqrolNVGEoBD7RovXxu6w3tq3e4XRRVngw7QRaLbfhvFiIzWRmxcQYPJd4kjGkp40fbH756JH4ogOl97wB8OP2zS2DXbbIFuhr366v/9GvfqGhePbiudpGyJ/qZF955+dW3fRNc88Uyjky9h00xUYsRDxB08bWv/w3/7/RtsW1JIcVi+N2VEFICiqxWzGNfhRLlp6v1bJpcLYcK+Nsmbu7lmTap29ARmvTJbNCNomLfGBg0xoLT91GZcY0MwNMskjzycNHf/fHP3u/baKaJdtZ3PyDSjur6zQ7tBDwoAyLCJRxjAJPKXgzxydfPMwfLJUNJvC0Hyqq1no3VC1fyl9Px2jD3CW1dET+xb3CQ34lfEihHZih5zckyDfgU3Sh0vTwhmuKpLWB8VGRbror3IP6J0HjjPGb4coau/BDNX2nHLmkEWcOTmKq7iq9zg8gEqdYcbZLFo5XjlD3KQubHHQZHMcn3NCkDQEyV9q/l89f67GwhF6eSzTra149Zq9EADc6xcwLhp284qWufLUDj/fu3j15faYtdM6/N9mZXuCd4+jgF57dKzx8CHdwivXDuG4C7IihcSqaILB0kIZjrOyLdNiZrtfVp0ek5kS+nY09HtxAE1YM/dHqWFpeg1+jBQ5ZmJPLivLXtLgU9Xrt8O7ez7/++senP9663fI2LMRnDoe4T+0W/vRJ91pGjOGyACzmAdHKeWE8xwv3FWPAGw5hBIOJsBAAsOZYNlZBoVElNQPwf7ogkH798eTHZ08fHO7rj47sxwekUCTVmjL7oYUTA3h1mjMQqgE9vofcxtHRvaoT+9L+/EGVKh5e65vaHKofs8EekYe20lGDF2WOgNCr5a1cugAy/eoR/GGODsWxgUYoO/nT3MzSwyD0oH+KhH46RYyVddN3eTwoYxWtOY++0QtnDrRjqrW0PEZSBHWaOCji4tICWXfthZPA2tzsMJVIrOL+0wPIA2hoO8Yztp4FSmHpqoAXOS54rMpVusILQkstcoZmhXApXvIZEvxV4Zib3rnbfvCU3odiFPFuK/OXRL1PQ4vm/EUhPDYDODy698nxWVrAW1ssxyDd0Cg75leI3OIJtCCTdMY5Qz12IsjXtZjx7u6dRw+Pv3n82AnKD+7rKN/5Z//yX5ycvJ5lo5Z/itDs4ezlJsNJ+xmAX9fFunz3pljGqwav2pV+a0ff7NLJuPQw+KYdvv3mn/2rf0lLh52GSRymtXGw4/Wn158s9e3sFrf+sGsQGgZh1CxpGl7H5S7YZ02iiESioaR9ig7Lp0EgWgbXKgzAgVuEraPz7PmLdz/7mdZKGSGFKT597eF8J59xKk4TuL4+0vK2z7MVKYkPh8DAMnbV0T+3dy7entfeYdsonoltT6HEvMfJ69W0yiIFU5BO0A26Omocx7s+O+2qj/1LRfFLSkJZssWG0ZhJk3GBiQV2Ub37ZNTcMWSkNQajKB11ZhANZWkF30vF3Nzlx0+XF5dpSJunhyRfLebpHQ4dQD3dzZC+WecW3r37mG+4s2uqbk6205naNsXuzecq1Xtm9pyucxeBETgY0rA6y8jmIqAIp2QLYQj0VxAlQfZYssy6wC++xOAWGk2OeEnTiRQdTa22AL+5izmiiVwInJd0KP8wA3dSgBbPVos2hTz0IjrS9j1XNkriM752yTPsHdOLy6VVUsbF6d047f3//H/6PxpY9v5zzYJQDM7/m3/6T/7Fv/zXRjKvOqH0ihEiSVXJOBuPMDy4NHjiPDJRh41QcxoV72hGR4dFs6wqhyOqkfsna5xnIkqzFpG5hqgWwiKH1Ej7BMy4eDUJaxa/FZVQbXxYvZhgakssYt6hrbXkx/kv7Kt5tYy8TBlMDBr3grOvTk907e9+3DW/bwAkXW9JayMDwhIG7URk5gMZvTJPPWNjnFVOMO/ZTtGD/Ttnb07TaoFfUw4FI/Gxed8PDtrXV8r2zUNrUfAnJq2QHhjQ8c8I/XmrO732JnJkSCo4UNEkAjBiR5tHVENQLB/RgtRwGOfL85GzDqLYwOyvmbLvv3+GoU445dkCnApeUWsTZ4IHqBprJwnq8+DxIysS3l5c3rt/KLSNZP8Gm5iTHiUJUEUGG4cbqujVATo8HR7hkBinNVqK7D2o746PnyyEoJYpphfYN/9JhJrjhdSFU7FlYYk7ecq4XKllDzWJLKQd51Z2hCq5kIFZsw/v3l592v7xu+9Z3d3DZrhPjChueNHggUmGV7Y3HlsRd+vF8xc6zAdHhwAuHAM6LRo/A5H8VLFmpoLqZEzcZbgxPPTkwT1JTryESSdMXt18+eTJV19+IfzN/dMLx1nz3zN+Ey0kZrm/3QUteMATyzG89G3p62oSJlomMrNS+44X3bG9DJW9lTxGKT+d5o5dc6rFkhgqDEBZ49TchG82IpDK77OTFeemmRsjLqLQUssC5oqncROUlVDH8CnWje7/28s3XlaydMcHfURhSSPrllMo3sIbSyBvpYKGIhdTgkAuRHfi1q0vHj747kez3dP6F/XUvqTamfjWyfnZYwsWCrJrFnLSP10RPNd0hS9ODWveS+ilhaP1G87bu7N39/JNb52a4j1Cd7ZBVKkqQkoaTqx/7HTuPep4+vrUUkdqQa3ZEo6fn5037xErPtcLm1mMbUE6E/TCsraEf/gIc82FmbW69LIXdhqYbXnz2tVWx3u1LLqwTe0zz2n2cN0wl5gEj2yBMCFTby9lhVxhDSxDOzVMFsongOgEnNvyLWuVlaO/2PQ5Sxm7X3dc+VsOz6cxsTcvTrhkQzLWNzNC8sD+3bt7ZnJEfJya980ZVqp9W1szt6AyfBuYzdgAl6H7nXcMq/muqkhLAtJDE3frAMQuBuyxVQZXFqH+zS9+zsDIwNDVALC+xjCJ+CGqhk5dF56Uv5/ot9YrMMyGXyk8sVH2jr1Y+6cXZyNSI1fat/Xtrat7B/uaC83wb//4eydUwHzC++WddDFzS6tRHYOrCjjz0XpVMAGCXl0r5i0IpbiR7WLC/P6dnVsHXhYwQZuuGTvTp+ml0rpe4+3ldLovy2P0zldWMQbNo5FZQpJibcWm434BVnnCWusFRBoMzymQbtLzly+/+fKJOXnmn0LkHV0hCV5q3z8s3hJ41KzfzIo96TAfqRmz5wGoYrwe/4MNTbAlER8xRc5+JaACM5rBBu7dPwb55LUlaGYyvRG+SIlo5Rw2palO1HG8I7/mPUQmxbDC8iEnxi3il1NVEFRNtkaVTetostsi0hYTFu41Q2xYzABh/sqIpQqkLxSgcKVmhJT+QxWerUFYFE9qRMk0rmuVubz+k4fsrrGaCF7vOL2iPYdNbHzx5UODGpfahI+dXrrt2FPVbdjztDfBVGWNIMXlmU4JYtaY7Y2WE6XRs37Mz/JRqKk89P3E+LzN0jh7NBkAkaSie/cOnZ08ovcWUCMovPAn58vySvWLorVB24Kc5Y1pXEtvQnCmshlJPQcjYWsGS44PD394+r35h7t7lPKuw1N+8Y2Xlj8+PDzC2H/+r/7Vf/3f/N+KFUeH80GtyODcYJfH7dA7TaQL1gthah69Si3iW1yOIpnrKVtKvbOr2f/qwQPvzPReBjO4cjRVl6ANGCN+/NaAm57kppnmiKLEsw+zEZeqGy2OL2um/XUV7BomYVA0gLMsBI5pkKOCz7zSoqHauE+Fh3ETZaXM0Ms14GOErDV4Gqk2P9fOdgKSZcaOXSID8BIAp0skCE1XQuSzJNtYLBflZsPWoTx7+gIJJjqreK3TKDAFbgv+i5vPG69de3uVVhROdMiyJcQaAcQ67Bys28/uSDL+QmNggSdPbAlDI4bIwoFHR3DYvdte5zhPtxolsx6RQlCJ5BDCY90RUgCQng23hwy9bVdSo23ALFLA3k4h0aINn5Ior99AZ0P7hE84vE0KYGMdRRmtDnK4D3eqO4uqrQ56EOLb8KQSMn7OqeqeAhJqg0+48OIWvMyKLELRrYKHJhIUUaLLCCGR1a7e6pz2UPfMf2v154gJfRv7GOAroDEguu38temYAS0fHv+vf/2rwzu3vvzy63tH97549NgyeMNf6XmYrP+Tf/KP/z//6l+9OHXaL2nFJfjDxB6FOgPhOjyMqFxcqKMjwt1AY+TBipxcdP/43pOHD+8fHv7syy/2d43v3pGBXWKzuQk34LNd28+qwNEJUGz6yWjDrilkj8ZX51Gc7kiVU3JK6S2/nIqDBba3zi/zlzBQO0HFfTpgiObDe1Xcu7tX54gn6xBZV08XkeRcDP+9/+SVZ5tbx4YNwY3/QhHHU7+xJbJFdYIBSAIRebRvaAeotO67gZW+jSp4IO/UgSbdtVLg4YNDb3GyfScNgHhyioH35l3ohH10v6gMGiT6xRcPPA/m0o0e5fJbjLEkA7U3RzuCYDgfTyZ3Ml10CH8+FyrUTjfkgHrYx4QSSW8QjxXKDUOTO4rKisDKLP44dZxCLMsNGTGzem8tBCKpkXsRJlYqlNuqpml+CU6GuDQVrjAYdFRQfRQ9XRmRpXhT8cLNOFVWEhJr120N7eQqtEnOa1vWv528frlQVaHMJv4Ck6jq29QmgAtngzQyqEz0EsnVH/d++e3Pdm9tfP3NN1pLu6mgk+MEFGc21o8PDn7182+f/qunEkbeM+tBylxnhA03FwqrM7DT9A8TlY+f3mCwdes/+/m3v/jmZyzB2K0h4fjH90PUwLBlbZo/EPErAlt56pS4+OF/C35u31ydwd5bXgzB587lktXThs1xpu6gAaQXFghF/hgj8IQ7UCRZ0lfbNV7PEWnZHJclQ3KGCLuKnnbit3AFNWmD1VjYpP0lB/3CCByag1w9g6HUpO5X1dkt/eCRPo9y194oFfCYrnPs/Jt8mHvFF24pFfdomCZ21o/wYZ+bDHldvCPXS1bjodM38lsVkmOB7xt7wmDgSoyZfo25Ku42fOsXKKJB26wTNz9KCIVxowgoFTlld/mWNsl1/eC7WM3QPEFkTKZ5E5cm8lr2tFbZpQ0KYgR7pN6Fs7gApmoUiNtTm4TwDPs8AB8XBtUU/sqjfaTflxTKKidF0k1/8fIpKINp0W/lKxg8rZn9469OXxd7N2ASRUxC+amxgVQlhCpHB4cw0qeRAapZ32gyZmrX/+bbn/+Lf/2vRTU/CY0o861xME5lN0ORSkuMWf5HfU89NrP9lT7+40eMwBrXHi0tjIh+a9syPt12BeI03FJOAUZVpOoNSxfRGuvVwGEaxc/fpOcGpjJuFVHfgznjxH0Ci8hm+50sb2WUdy1a3aSUskSULi2OK27JNdKvsXWoxAGyk0V1J7xuEmpuaL6nTHYYR7F5BFkmuALkGyGjS3lTyHIckbFYnRzyZjghMhWPHGKmmu3ZA6dKVZaE1BozF/VQdfcyjMrFYcBkFv8EVO1TNoRjvKday7LP/ahAeWp2JrOMaonzDc2F0RBQcv9TJXC6ixDDh2FZjSEgTNBmaiH0njGdVB3kGslh1PMQk2febQeKwRazpDqJBhY7RycOLAJZqqt6ZQYnSPopQdLc18SVzYABxYYw7V7kBsEmXq+cRvHRbh6mgljzHMTJezgWDSnG6E+/a9uQNZ4Z6nheMSXfaES2auwvVHgcH1ZkoiRbepXGy43rn/3sa8s03nzwwmzaVfzmmvV5C8pglBHXo2wYCPWcQMAMYWy0n1V83OI2sAlHeMOJp2ecc4e1iIVseDCRLQcu4/NowqJdaTktYgn2MiSM2tBaRlnT2njnPNotrwe1UNkwZa/bsIL61jYL+PqLr+zfYxNnF2/Lmgw5LRMoFYenn/4Ro0/PsLjEEXht5zCiIu0OSrbj7VKxWtyIliujHGxC+Kd/Co86xOil1Gd4Sw19Vqr/U39qETN9DgaDEayKLQIFvWytPFNd5dMeX1U04pHijgYv7hLenoc3TQ21looFPx3tvXhNFPImNhuYKkVUtQjHe0eoMR+9Ix0eKBnvMn0RWvoqd+9qYGXTWJPw2/ML+Bjt1WO0Y87+qjZqvr3Uf1GdqWjDxA02VGd7G7gbVhv/ZnwQbQ2eJ3HP043hVahGqgcTX7mBt8xGySyTVFeLbfGtSvQ8edgd4evtQ+sAGhDi8hE42gHTDgcxx6ebsXvLudZsxFiqN+rWDdMT0IBzbKIm1oV1ZiWcDuR1yTDGB0CwRbBtvblT+M/eviEirMAAGG7tFrDG8sF4kV96gCkoyTBG0Lww1r+3CN874T4dpzXm1RpCAWXCwhGLQkbeDX6tbdciAKfgeO1Y4SmAbZKq5Z2BLwFqb6+ohYVNUlnfMAyl0/yLL798/ODY8l3Hqu5sWWh1Fwj9BMEDRiBNWIm2ZvcUjMg0bzW0mxIFLbFkyAksNfLl/8oyKFlyTR/ljU9xJXL6DOrCByT0Y1Y5eATzVSkIJeVF+0HIE6YM6l3anarspysPN7nzjV0e4TlRLD8BqeLBt9vJEfPh5X4cm23Hr/AQ2wWQp6cXeo18j9k3m+MSlyNn7hi5+kQ3uS5/C7RCar2a2SwPBUt3wK/Ho+t519AwlKmRkZZW0artjq3t945yUU4w2L8TvaMFMx0+/r9T/XqlC+InToVmWUgccbFhfkfg0iCsGJWa0gKlpJs7M5ugm85UybA+ED3a2rJs8YcfT0wrmc2ysAs5nHzsGL5ZOatFo2NmDRpdx1jDR9Ss5QvFB+OzW81qxM/6xzYEfvDeoPYm0j75mSim7d/Zgy0FlaJXO8yD7wgfC0ZRG1GClH9aHFfCGQ+qPt9OFb58+JBHFygAIwNGNrxfq5cO8UlNWyJSYJTRQVfBpkmaxNj0kgR7Xwp8tEhK3WoObrSZF4eVRam7dw5abbj/4N4DzZwV3UqBpntgJ7wD5madCLxoCdhsh8wWhVGeSox+r+SxUjU6mTJFZFopn5z9dOejb1zRD0uKpSE1HgAbCUjTs1nQU15Z8pjCDXDlMjJB77ozdFwVMWJlWyD5oZL5ygCq1TU88JD0wkG98WpBqfKlqmTQyUTg0+ruKYtGsSg4WfH1zeM9y3UKmXBSXzxSxj4NDHgqCMYhDrQ0x0k4kKJOWI5QKx69+YFCkRBHG6lVYWTO5yAVDf0LU6viMCF+TIFw6t6jUGoyuxnMCJ1/C2Q8KmUyuvFeAoJojA2Pow5Lg2Os849//qPWTFViGEGU+fnYFKVNM9N1b8ExYJN/wmWCGYFSReGrGpg4HbaerzHWttF7kdIyiWkwfFOPO/fhxSgxuwunb7FBdUO0K0o6SMdtvaDkLYB0Ff+kdp+cWvveu3r0E2zRvL3VBugrq/o0rbalcef43Wpei8CtKAwICNBUfXFBKLZH05bZZTJcyqJGI/M60KDo5jug0npDZTWFjky1LSYEposvXhIEvl+/BNYyvEE5AjxeSb+QAx1xLZzy0WxABmQNPmpVoCvSpaUGPZZVRt8Vn3ltlUht3i2NTBM87msxu6xkAc4PljM9mB47qHoJBTzIXqpSjkYCMFWnqbmoFCNhjDLUdqcngxeaPGmgL3QC60YoTG8IJrQZXr7JbQsC2NWCOZjTTg5VA3v6HQtQoqWqcaKKI4OGKUeX0mxd0pLHtQ/+ci/1l1O2mOBuotpgux+KstupAfKhXb4caxwa+n1Ua3XNoxyJ6e0rGshnc9lDBxtbm/C79Zr8X34W+cQQC5r40GgI0a3VExAa1gulzeWkQN0GsyJqbLyBngBrDbZwi9NVa+gURlr84j0sm4Y9//yXR/YbGWk93D+wTa1dwrBEewWqLZwbUptdfG2usZ0/iUWWefKTi9NnL581TLTRFtJao+vOezQa+/zFi9//+S8vT84cfw3UTIa3Gs8ugfhAlc0079x+fSK0u9pOUuCqV98/wWCmTpGKTRcc3LWRihpsyu9mQov8LslzY+Qlyrx102zUSJ2EuuACe2DnPs+U5LE8IXHekhddbNwjjZp0VU9xBRdTSZaDWVqrzsDR7KyNFQzeS3swxYbJqwd51jJTJ0AWHxfYICieCRXlG2wLcN6wcYIYoVB5lq+pv+qEgKkIn8jQs9iaCBROxWVfYBft0YnqGOWONrbxE8yyAValtXDlG+yCVTSOLhfpJOguUNAwsMgm9chuaUV1DofHKkij+MJTZYfOmpEpH9dWfJ3qBtz4C+ktrwC8AOb2HQOMn5yACWHS89ACGS89slJIfC8KKLw2seOJOgZ3g+x2xterdojoahr3gxEhECzgWAigJHggiuZY4eMsJOugG+MZj0bJ/+abr9+dX/zj/9U/clyNiYE2tcFIe9P5ilqrKAPQt0ZhYGKD73G43drh+v79D8+e7ty6fX7HphPvNvxw8fbyxPJce78dP2911sbG+Zs3fFQLgxbx+CyEs/ajhsmkicv0Fh9ZJ6EpEo3GeDoS6Dyl7f29/So1aLBcuOCmRkYabG931khzlg2ljYdbONCnlmxViryT3JD1U1LWlHkARWqRmXCLrxLzXBJdcd61rIyazDRX2ZjRFV8qAIL0sfWV9vNK4yNjnPTap0RJD+maG6XiyGhK5hgC5Rs2LZo3WYq5B8NVdX1JyVuor8phMo4sdxYWiMkMwlt1g45cAQ8OQ/VdXR4FLNyruD9AB8tJ9yvkPZ78NXeKTwXdVtCPJR4eVavCMF/BrairhKyIwc1svafSJqXKdWDkawazFxEvut5iTTvaT09eXt/doyF48vFqzvDaNEFV3GsRyolTab020is4end9Oxk4/DIPH1Rq74QK7Ju9uS0K61hsA0/1oIZ1TPr+sWF2r/VwlKcKqZkhTgqm2+Kvs1Dj2LCiO6xeCExZODLPGv+4/uHlq7M3HW1NoQ0UTQAdt3UDhFJE+8b+dyRoD9pgkXUucDFPvYI5rbkCWgZDT8CYOxxOZGlq1Ort7eycv72c6hMIIwbPWEVnGDRi23pPaGsdFABfw7kogdzdjgRWtAxBcZ/mJ+BEVIaChmZ0wvKTc9tVsoSF0mT7h2s03U/JcvRoMqwY5SfpqhcN9AkaUJq0qWwUNqWVPPpRhUxad7b8JYFAVDwIxNwQavWkPx7GEPVJWuENm5hQMpgyKRKIRTYVqzhSlS0jIFMiMMPm5pFF4bwIR7jVWneVzGCocafLbS8E1r1WlvybHWmplV6nV3Q6pMrUpCGTew+PoXXy8tRc793ZnyA74BxM3mUYhU3yIByGixkg0A8ZINXAV5YQtyjoUDBKMuZ9sG/BskVHDXxB3yLS5UU7hfsNMm0YCDs5Pbl/sE9009DkHwBPotFrlHLLkCP9pFBCJjcGXTREEz6Rw6ZlGCaHocMOIKbDsuGEHVgtGAfupwvEUv3Rs4wxr97StzX73F+enZ50csslhNGMWhdCK+OIAW9dGKc70mopudKLRFXs4HU4QXEqsHKp9qflaBPPxUGDs1smwrpi3SjBokkq8FvDArFMN5mHsZyp1KCR9hQb5KRyEz0iJ1mDMfSNU+fTWvlYTga8AOmxEvUxIIwwxYwZ5dULYlLhtDPsq5CqjQxk7Gf1+ANDBeqtbjnlmqf4UEJ+GZvwpEFsNYRpAXrEyNCmaocSLPwMhVaY2WXlNkArRAciXFFI0RZCPj8FMDx7Q9L182cv1RhroyBC3GlRXzx7QfAM5/z88uT1BcrEKg2e1m/ocNmFVxbnGeGwT+Dk5EQplYmprXh5c/7m8N4BRbMzu+paqfFusI8BEpCCnoXd2ZZhmASQbDygSDERR9KEvhRBSNRZknz3rg0t4u1lVbZ4f7yuhboqpK2tuO4495bR+omkOaqUKQq0RltkMHYscsYgzLZTXDtQ77SnoSeaMhTGR1AZ7MP5RSdSbhgkivoVXQwFusYZ2FaL48d/DDfVN7LsI9EptZSJ+6nxtVVDCBw1aIQ76U5WtXLnDomAEzLSjOwhTcn66+oWlGBf1dW/0XoyekLVM03NB8lQY1FGVNXVsxAvrOr55Cmb/2lGD8eaAisFvEUcPZRALhFNgxdLDKHS+wOVlLR5uKmqmvLII7eUtWx+RFoQmbQDE0SWqXhQSvdGEsLCWxxHWdyudOeKntgvdvryBI25mZDSyt08//ElkLwk7qAMUfCwlPjHH19gRLgFNuB8of7fZPQAJ1c2Of4rLoyrk4srjz6Ul00De2vTSOVe80Jecdlm5UaTbuyfdFlM/G6MVyXxkBE6bcPqIM2vTZVeo6eRZ300hCh9hv9yrZiWCox9Zs+rNGR3Rc+Ed0x/XmxZRjOGHbvv6bilOGmvxt7eXWt5HfhOLRgZONj+9t3bl+deRHGhlygYN9EnUXSNWjsIJkAarJPMhrG1iVdyJVZyRz/O58pIoRbRmnAv1cyNTC24FI6zLyfJU7LFTZVe18y/ZJrO1XzFHR89ldr/8nnqB9YjVV7vvQQfmSInV3kjxUc8w8E3bw0YX21vN9kheMbZMQSVm0PpngPhR6ohYw2B1GuqTDnMzO3cdg7s8EiO/LUK5EbvKByOKzw9uQjwXF823KEH08npswpAh37OQq6wxSvdnOzDLXyG2JHi5M6uZifMEF2SItzWyxevwLrb+zYPCFUp9Tk13tDx/tFdyKtBbq6h6tY2rNm2V8tA24e3H9VFyQw+89DX1y+Pjg+EmS+fnwgmHSlgZRrFg4mQihy0orF09CwLhg5iu8t2AB8a62HaUPHeifZq9SBWYovH7fHi6+xvd07HbPa+MZnlzzoFCK+t2yzvFQcCkUIAvnd7rR6tFdnpAMU1nH2zyZeNXNQr8gS6gYDYoaJ4jqZ+ljKiGRxGDyvWMLQy3IRBTwtyO0w/A0uO2gyzfn/8y5+ETR+v72ipNk7enl68fX7y+vunP3qrCxtxFsbf/vJvrD2gZ84CMYa5bnoadmB3OWnX+WLNOW5vt+ByeB7TGIGf8G0M6tROVKfCaFKaP5z/hQc5s6FisMdcJSLDxziYuQviYiFoRapKe16mLG6GpfHUdbC3S+p8xvhq7VoyYJaMT/Wua2tC7Wy7hQUGvJM0YFSvRQ25nOZTFBkzLlaBagjCa40stVPNLFQEEou9hkw0pzElDfOjIBSVVEVpGUJZOZRwG+XPxya94ofJFVDlBv6UHtZouzihrHI6iDKoUNfeEW52EXC0IsPXJxdeISW8Tp+u1xxb5NVEXv1dXAynm+Zr5eSLrL68uLg8O32DGlg5kVtN8SkHlvOhlxa28OLGT9N3e09o7lzgwG0ogvYKQ9ggz3PIgsMdiSIWMrVXNo1akTanfuRsaIklhuA59rRSV43fc0rqMfbx6sXLL756wpZOXxmyPONEHWTmsLP3p+9Nq1lYY88GVTPvA8+cQ1dhJauo+tjnXxebjHkZqoCCLrY4AnpuWlC9k23nKFKQvnm2QyurXzw//eMfJGoazBpKxVtmqQIhylv20YqPvdrqtU7Oo1vUZipKb+bkC1tAxV3JkaoQh0ph13IUpzRvb9t2Z2b9tuPhDPAUBi1Yh3zCT7pKVDyKIoXqQbFnK1uRE9qTZJJhVlyMtUzm9Yt3l89f8/rOlFo3BSHOaRgpMzCwxfE1AGWg6fDuQX4tN4aMZjbUQP6qDKciFnXUFsEDmqlGCOC6KdKmhIi5GoMRngvGYbvCrdSEkdJMJrzP4lVUxYvPilM56YEs86whVUuiItURcWRnWTSU/fuSuoILEv9mluP585dUiggv3ryr3Tt/6+WICh4/OCYG7kcxVAChuWtiC61tgv2oBRCsCNylW2NyeHR3c3vz5Ysz+910h9sd4fjUfIeR63iVsgxBQygk8XbVvhEb+uJQBNbB0PQ7OtcYiSJubu4ae9kJmfW1g6N9qi8jB00b9q/37SRu/+xtYzKmpHUl8WvT4V/WjfvEmeawbWnzNsqbtX1HrI8rLBZKKvhZWEhXJjkRQmMYpY3vEZc35rCJKPGMUzBH4EwWs0M75MG6cfjVXc7Ru7pTUL3GW16uYP1nvdu0UMfg6hMtojjVUKW9wKW3xBuGmSlU/tQok3YvjepVBB/EEclURDDS5IaCcHJ2fHP3Zqexo5gX7KLVdCZeBnz5l7l73jV+d1JJUxd4wpaZggqftCQlhg2xfff06aPje528bCnIbLZg9+eX53/+6w+/++Offnz+/J9u7z5+8ChN8Qe9cZfmTUBCq0pnILjlQ8Qx1RNt68BGH5HWHlyNjwa0Rh9CCxnBGnoiKxPyI5X/TFB+qR9qnbueg9ylZNSNXwN/0rORAFZmQKwKVcskiBWg1Skvjx4/IrVee85ltSinl71r2RYbpi5eSK60guTR+CF9tXb91i1ngujx+gVfMdKrl6/v7O+lAP5vNvwgmL04u7TIxNpYcWzoUqsBtWjbEBOaw6ghGt4boG08evwg9vBWmxtUgRrog3WCXZFwvhlV8xJEuyl27u53vIA8StibqqfoqV6Eef5gi6IVnr0W6tKNjK/a7OEE0lIfGMfH4VU+x8VKw63bteav5KeCWhdvKVLC8AlDMf4+Zjlm7MTInVsOx/53f/8bLk9Z+kCIVh7ozDAnDZTNzM5Hull/oio9Y7SI1lhMljBoo5fXf/P2olhue1sUuu5Vy4LnBqBitUbDxJkDSDc3Hjvvdjwx/yeamGYRZv0bLfExNh1Zn3mNpFyQK5I8AHQIHotJTXBRwRd2vJ68EpJp68jk9Ozixxcv/vr8h9enZ94TZcW4jQrFcHP8E/0WmBf8VFN1UwE9hSqQku6rtAfgIzXeetf6FotvAGFstXXecorgB4mFisq6iuZIqAZoZATSPPBzrikxVa8QoDvJM8uIM7m+QYt7mWwZp2dSAU/PrkWudnHrV7abx4luPzx1JF4cX7txnBRz/eLL+2MS03NSol28GmVvsnCyqrfRvd+/u6M+A2tsxmj09h1w8k41IOtrXz65ryKcGJ4MajEEWiuihj9+RrIGBwf98KFDMFEZJ0rXKXeDNtE/HOi+bEAHayjqkZGe/f0DSA77+vI8OIarGyhXW3/MLdkMH0Kgyhval7RYQyBliU+h27Ic6E2MZE7g4fE9hi3e2zSJ9vG9ThFbytR5w7Ut79Hh1KXEt3n1BKpy8Dl+G1w3MW3pZHOyls+xEH8CwjWTsXGer3TqOA35pBnUOHI6Nn9qriUikqnYWPDf/j/+3Z9+/A5KjH5ajERaYf/hPHT45NJjXOzIk9WK4U45hpML7+oj40HCjRVyeW/cq7PX/+53v/39X3WO7VO3J/C9JZAcp85fwejVGpcA6c2dBputKLT5CAeTxHANONJpFKygP0zCrXDCpZry8buoPHtzLvMgCAFCXEDIVf4Q8m/BbB55DMjQmLwixS+Mq80cMEUgNW44MpXN83KVZfRryRe4gaOGDQpd3S1c31adT55pVN8iNruCas0KbIIYNgJG2zvVh8fHdvbUpjWyTvsPDsW+ScVpvCv4URMGcRmqGV+3KczoWWD73ReA+YQoU6agPy44YWGWGE2N4Q9VSlJAQ/AjP4n4zXb0HZE+UqVShnR676kWGLx3BluuvTRaM7FtLYN07UzLVGjKSiykNgMVYRzSg1IfEMLY4eHN/v6e6N/QkJCHAmCd48djuEwRl6id4eVUkRcnJ6IMIqlnqBEq4Ok8OKBfO2zu/Xucdjb21h0vrWwVqoIy8yHYYcGaBgf8mINQrLtuboFcRFxeef3w0eOzy8u//OYZglvPhJnyhMPwG9YwhtecAhB3B8cI80Nb4Jsw52eEpWd+DO9rEBDkpZE3V989e6rgSEHntANS8VhOeVXpCFHDbMqaS9faRbyKammLJmGtxQAyO8kJ8QRTi8JTl/pgS6dfnZxMUVzsX411kDyOriErD6EUpJecC7bLs+HRIDTPhsQg93S80dSm4HQuKom+ouJ4FtjQcavIvmWbo1NCXcvoMRHIXLJRhGY2Guyby/AAafcjEkDpqq/UZ8Djv+qTAtRcEx8OlqunWQNeCj3TaeFkgAdv8aS0TMCH/7ng7Hey5EhqzRuevLJt30mV6zrlugH3H9zj8c+MdLWf+ECHMnlC5Wbj7PW54Uicvf/gwasXJ9qp3T11rDsbPLhXdv13onOg4QCJ4Z075IRWqMBhbn3MthNxDpes0+s1f7yd1KqItTSAnOReN/7w67/59bN/+S+8ZsD7a64unT8gmggsRccoZ/KZc/i4s9vkbVraZwKJgY05C6Jy3qVDa8M4jhRFWis0fD0+Onz84MHJxVmRXv48AD4RxcgNdjf8OjoZbaAAPzqNnNi+kCUVdJYgkUMwtsE6zV2L1cSXI+P0MAgJtCOh5a02rsw0oWMGrVqNfmf0hTldaZy+DKmh5iw6G0dLP0YtlocdRk+VVKE9NfhXDWGtkYzmkI6ewWyYAmQ/asddkE2dJ89kD6piPcMx6cO7BUrWBDkPAExpwyV5jcINptLGow/zgVpITL/DouaFYx6gpWVBkK0V958fQ3gTRL7wXqzH38kRwZJA89u74EO+yFBiFjaA4aC6cXUJO9ziwKoyWUahonUIioOxGAKONWhocn3dChlmaQ+65QvOY7TKC4+85msxYzntalDqwf1jn4qou5VtHz6evj5RvPPD7XBYKMVAyEQ0TFW6cNt9uku1FomU2avobu8c7O1TTZiFdFTFBw+xuhyD/M+++JJ+Nv6TkvfOX/1msJtFWbsy3316dhpwCsZf9C5jA7tFJUGbtaRsBv/kcTmdDXfi9U3n46tCgPqLn38DRSGf8LEQJBWYBiUeR0yodDNNp9/jgcYHjsLkpqxltQRIvOasekt+aedwINMajo8cE7wSVH+wScKLhjoP7207GSKD+0+bKEQdONZIFwJhcnHRi9HSCQlS1kEL5ZubTo4xRBCWxDLoZgaDRvwdjqbftQaxp6ejqRERKAlZ6Zh3VC9/SUHZ6ZPEjt54MLL0uCyu8JSOv34uwDrnc1bgheAQz6qM0z179uLF85cICcOR6JQNI2VXYmuKjAe6/vD2w5uLi5CPBTeW12OLbdmGDDkODQbYqVbaErKJOK+lxiib+wRXFUPMfExCmZTlCuyCuhvH1jc6TMAhu4Y0Ghq+2Xau7e5Ormfokp2E4Ql/VWrUHz669+SLR8PLVouhfHhbdQspYRVbs0+YwWLkUrVh3NP+U5ajw8P3ZmBnXwEHAMREa5YPmVXIH4mlH9w71q/FC8qgy3txcXF6dkIUMXzWEQmQmCVGibQMqy/ROyXzXBGUmj6jUyBwgIaP1KLbQL8SpzV/m5u/+ptf0ST+p7EaHClrfDSEA93sGMYoUaFb/+bDl2dpPFwLDHtcVoruBuFqCklfIxftR+mdY6VUxgY/oh0L/Gjt6qODA514/TNkkyVYKtXOsI0yQhBmDN5H1cTKeN/S+KL2elTN73isplHfyBlADSwmCt0PQgBksNIENY8Y0hQmckgKtvOrRDiA81mPaso1CN51JfPahhNZK7XwJIAA/CdUe1gQFekppnOnvMD8dHfPSjIO6YOVXm0oc27FbuumrI6kiJQSSJrx1hs9HLp46XzSDgOl+s5t5m68LNQ2PaLR3/r6y4f1s1Gm5jQqTEZgq1/JbozFZ4KAUANxEyqFXQzk9IiPissAWSaqgz1kdZ4N54Ntgun3F5fWI+hlQuD01QmNZDy2sC2vVvCzGaFCcOQuQ8tzaygDtPBQab2jYZeKlupDLtTXb7xF7rvv/0It6+/1Bp1tmHC4FLK+iqjSPiHTYzs75mqs3izAGbhYW+wyzv3s7ISjoNVNU+4aATJZudYgkvOaGl28JQLMs7CGa0c4G7el4IXcCHfB5Msvvrh3dPT81cvZvYFj8SQuUSlcYdHqNZtTDCdwA3U0r5tui0zKH0k0J477nEG3zFcR9MiAT+VcNv1MoyZxQrRGsswXfnn/eP3giBlkYyDM1CPeOeeMYdbtR8PUxNvFTTqCbony996ULdtXqzy+h1JIDYVh5b/P7MEnqn2VMbxrmTybzMpgPqQTUzWUrVoHWsWamJTdo/pFy6OwGdGAHcjoRSw+uwlCVl0bjfs13dtbJ69OZZogaNuEWq9cudVmqxPHPx7s6/w5tQoPvX5PlOLkLy8IEGwWG3385M0Pl1dGHi0Bai9i1GSyYbjIQn1hHgJqXln+cBTCKVFYG4yfPKPxVthcHezvn56e6Yve3bcyedOUM3KdXoVJp6fnGHfkOEoANm4s49HNNB9+dvZs/+jA9MLlxRvQrBtNZxSQy/+44XIzX/jVfHyIhsyMUvqJXV6GIJu1dDu3reO4NLrPNWS4c0yBCSNkW/ZvLeaLYh8+ft7vRvLeRSIUdx6MA4wF0L3vxYnw3pZ7ME1pkX1kUiYbB7ZvnXx0YCRLyAbSnDH+TJSefvro2MVf/Oybv/74QyOVrVEP1XTmjhXRd/e8rMH8DjP4u9//QUCPChTViUJKVMXXMY+F81EKwqzMIY/oTG/iB2MYN5yeJzPMyiXLcdPbtQyt3t7qoEgQOCrncVGezvtrqevVJd70svtGFUHjKuJTfFafKpDTQRiAhXqJ6R/Qg2n5UozwQUAYTDYgytm/yEli/Q4pIGrf3CyVwL9SwV65vZ5MRuklZwv9BgaQzwa2pAbr8N4RVydCvbxcBlVM4NT4EtL+gdfhGkbzUpKtt+e9YQQkRCW2mNRyhtFyEm3B6X5rIJqJ10stSaWqbP0ErGN2pTHZk7HcQWhBbtpv2VNGj+vHeY0adnK95tfoDd9JU8wcT1/e7Rp8GPDwNirqnV97H/ve4fHdyL5yrNPOUE5wwzxokOwMHvaVDAAbV7gyxJhZcw51c5Gd1Wl1/bs2UgKODt6u9W85bY0TGNp85wf/6fvvk9fy1p+9HYcgfvnFE4X/w29+Y65QmI0noiwsSgImtVQ74YwfTSniQUoTcC8mNCXSQYxOdM+vxrYvHz9O9e424Le9bBP7yvtJ7h8/PH5oOQCKXp+fe6n401cvp2HC+IrFTr+jOT7407pJBt2nn7UJiWg+EJB2sbYhBV8KAeXKJ1P4H1++vO9kMiEef0GovcXZtIv31tr28P7k7O39449HK4QDVP2pHtqrvGHZbV2otCv+JpFMdNQ/cchEHn7C4DNSP8FARrD8W13dKOIaIPCsRZSahZF999Hfr8KxIFVj1Q6QHlR6AGW3XlH1rnW/+mMOJmmVQW8WNOdwcZmBigoojDkEPVfu34IIFkOWHTe2e8dM8K3tD7bVi+O1jpu1IWKGIkMcyN5VVFXjAMYyhsrleaSE6oIvy1tpSa0aJabXqV67YTXSliGkGI10TKulFuvuDA0PnQXZzFpB2OZNs2VDpQhsi8LyujIPoBI+sU/lw/k8hH+ZgEudTBHymZpjWOd4ASGwIWdqAyC/QBUauXJ30/m6v/z6K7NpVgwe3b2jifjqyycapJ1dq84c9vDm73//B8oCedmFRoh1r+soYNLEkbrR3gGLXBWuOdZ4Z2+vuQCvcRssGNBdLyy2sfv/8F/9V46MtIHNwPD+7BSDNqY1antt9nHv5sWL5pGwItp8deHh6MDcow/a6MU2IIfpS0yTqPqrtIvwC7d6MYIOdtw1v/bq7NRqgnfm3tfs+/lol88Lp3Zd2P/T0u6vW4cYZBzP3qca4Lgc1INil7PHeboAS5/qsLvacucTuY8exP1Fa2krQS5rVEZ1VTGutRz+V07hfi1STLrpwSjfQmgkpevJfDKGYY+oVJwK1TbOW2nXKI2Da3H08p03/Ui2iYrHVTaPbhTccqAK6hU8OKiOAFgseT/t8bKzlq0MX/nz6lNh+LhNc+s3VHnpRDANsme55PnKNoc5dILgchtLmOSpmzEkYDgnAGjSqLhTg5hFEOg1oCqI1PF0MsSgRZ9zcXVhk4BaMtQwm754h6t25EWyC4NBqXrqu72/dqbL82fPzVbc3uAFvLPdWzQ5jjvLkL/VSGz0iwf3r99/axHK8b1DEr9/fB9MM3Qk/+XDh3/6y/eXlw79RZaF6/aBebc5r5/vM3uLVE5Wt1ivmmHjgvFjQwKyN6Y0nRwtNg4Q09avfvalmTbH1bMk0w1xLXbqVJn97izYNAXyeYTmb/sZ9xMITlkKAj9lskv/3fUvqaxYJ3tsUnxxUHHfn4W+dgzJ++fnz56envKOjrGw7JaHqDKcryYAaXnrFsOhOic1+GoIlEoTlj8ucERFGFXvmgA9TLOSSg4G3SV9Apw2NLyqaUwmUIPsUFCFspY96a4qrd4e9Mj9AprOTP1+9khWitIGK63WdEiN2Tm84LYFBmZLbu60ozVFa6oEOJYTVLdoV3bwcR/Xq6lqYsHQIMNwNaYiIXyHISHgURgNgvGhprZryqjCBF/iWuE6jFw3PEr4xGLM7o01f3u9rFERSAxSRsC85KaD296/ff/y9SsHg+/d2fPOI10dIYXGKhml7mKzerouvdXhKyj+8G9sFhpojBa51ygeRST6623LTz6u79yy8Ns5M2IjgZHqMUiXiR4yEu2DmSVgWvHhJdG3bj28//D+8bEVTNoTnQihtB6yxhMautQ6zFWFqq0N463b1jHOGUrLCu0ZaNI2tBhWaa1uSzpnwiv8KXNfuDRajioLy8ANa55utCEqhxoUgmTMv4ZnbCCZJYUlQ1/ySJreFDfUwgEs1iAIGHhsLyim9/WJx9sHttlKLONXajHkhtFY2kg3maaC1da59s0gKO5HOjQPYTuVVjFQoRbXacqgUsrcLdKJ0NgW5oHN6qAgS0+SZMVLXQhTB7kuCHQXY+I1nDPV9DfA00YO8Xlcl/I1oi0ndRRICEyFPaO8yjfI4FoeyOkfRMePug2x7CUk0F7OOF3rD3KXgmG7OAU3dRoByQzCGYlihhnTkdWGh0Yk38zxlV4CfnV64p2itw+O7l6cvzk7f2PND1da+65wkxrWPn3Y22q3LZ/tpGTKaxrn7Zv3hisw7O6cM6uWlRASRTwbVqtu2FsoRSJDWVvb0jLjQtXQdMGMpHNdM+IZiVEvzNYz9jpjTSvkHWTYqJrRWwrMVVvP+/jB/e++/6GRxi3LWgsf9C9TJ+aQWVI271nd++OPf2RKR0dHGG4dNEltfjRWpCnrmEYu3GaGXAFp+1ldqVgMhQYNxT9WG3kJwQPElmOYC8kepFcorS0Yzi/sGDoTT7zsEeDT5BRKksrVO8OC+doRb5zzv985N2qdfGVwXrn1Z3CNcSKr9mRUazMxUEFtdFvL1nOFYbdUGIZdVZC7ZIbTxrB+qYGoQPgB2+dK7XrotLWS/U8SbtJ3xrKUyk7DXLkBHuIEWD/Pn2uqWKBOgvQipYpD7zNelW8AAGPVHQfLbMj44vKNOqdN3/KKYl5DMO3nea8pWTs8cPqQvMlYqUx9bCN64lzkq8f/0SK2lxWhBetkjropj+3LT77GqwYyksidc3nTthFzApXcynBbr4x9OcMQnHdnZ7yr9vx4946BXS+c9lbFmBPzQgKDQmCIjU6pKF1GHMJFTiSGvD6e8RJhsAMc2ACcYdE4QQehNzEPAysmYAtIkGdRY3S2C0UXYPthlvCjSMxL+nSdm53gGeuppq9CGE3Ig4ePfvPbv3OOvN0X+OmpHJ823olw7AV8+er0L3/9nkNu3RF1UqR9BOGZG8YTeCmgf5+WEyW4YcYUoybbhXp0NrjpcSri6qGPYUBOMMcsYTrKI4YRVW60WFXeGW9Ot9IwMkiXelGpHIHsxfYfP4w/SzyGKUYTDLOahsqFNGCt5vSyD//r0kFt/vcIH3NLGe1KtsmnuisTz/wKeOo1szYe9SARBprppmM2RdCSbGkld8UGbsXJoOzdVkufi1rAqqJVOTX6KJM80lh8SjN2Bk/v1/FnCQCHfWu7wTSDlRy2VTpGC00TjcmI8qtpgILDxPNTqfgQY4xPDUH2Bb+ptumahKK2aLLbDAPTCZuEW7e89kaQfWvL1icIvN3QfS8wrqW7WbcTwFko5GhH2+G9Q1PR3NOmdZ3Xa15A+mzeZiliUWeEM71QQ020JV8gZm+F+mMDSU8LqXrS1CwYSC1Mbd1GL1syHmpjEjdPHMrSXQuyDfuu7Xq/Iy8YDZyIzBqTY7vyvXLq8tIQok73dDCShbGFJDVribyg3kuxvvvrd/a8WN297biJQokGhP767Icfnr7wajkps/4pndPFyOPy3A2GQrPJ5yuHcAmftDeowhrKl2QNeqE1VhN55CM5XZmbhdk+63DNVLRvdxVLfmlEekGNwGzcIQvx0+WpggOu5lHY+kzv2dDBTJRMNiFB4aNHLsxoH1cXBMCrDppb8wJYCgzh/HniGfAoc5c6+KrTzCtLqd7gTy4M7CYVA9zDenjmV0KzX5MJeD5jCMnxeoAZqotR5VqyTgY4DOnlWe7SkbAatRnsEa0tbwrRGLn1rOJSk0ZMQkY6SmPiVR39TH+KqGoBMwayAP5c7/JkZp9HdoLbsK4WjxYWz7czIe/wNu8vDWptmvc9uTltVHR93WthkHhoW0KUFs9I1plUtdFcjcnzF68bsbjjFIn6NrEb4L5RFjb+8jBkpEFaSM9iZ9xonkDD8NTr81M92q1dJxR9sGrAdKNlmoRofwLuodfUgdda8xe4XLBgXowtWYFweekFVY+ODm2GSROEPLO6mXFrwbQton9+ASt/9s3X/89//i9+/8NTWHDxeia8v+lni8MZlN5z4aBU9cnvnWBxafyilAneTLLUX2n0Aw+Zdoh0JgUdQ9N0JLwD1OBUry2sxdVbF8eNERTiDDuwKSYNq+Z2uUsu6Qa3lhszr4yYWOeD5gLl0fn56XNHIN47bgARrc3GClZsQdLVudYsIgMxElOPSixqOBXDIGAuPB9FnXEVv2GPxdkxt5d+dMmrNAhkVTelbCjoqa9IVkFCD8nlce68K/I87XPKdFedJVakRjPDWvIGYp4Nxp54MGhiaYtG52VtN20vvjftA/2TxZoLOuZfFCoU6gtuwIUDaP6LQ4cNnoZbBSZbOOBp/G0WlurYwmbFkSktcuOMnVlvqaNAJWm01NfLLjjHNeNayW/jxnwvPbZZx7GTAB8/OKKUZsTLvpCvoipEeQj5iNV5b2LzS9WJA6rAErtfy/GVmn0dFe2RN6rwvytuxPMAGmJ6+byVBDwfXbHs6fYdzaOY5JP29P7x4YvXpy2H2bpmRY4N1bBtX/m0hMdcTcHek0dPvJb8D9//NaHXXInvtg50IPb27N3207Vl/6oTrp2gQvWT3cfaHahMy/CpSb7dOxctw5IyCieK9Qb5vV39dutmvbXkLz/8+Ps//pH3x2LuZAwgXUF/Eq/vXgwGZgxeLpzIJlaMcc7v0ozjVjweZEPhxrr/dz/8+GzXQdyazK2kO2aTJfRmm1QpC0xJcW10O1nEcCkJo1vBf6pXck1ED4M+ze8Ko1hk9qghg9RlNBeI6aiOEXEmCQMdaXbeAHHg/ESQJ0Ak5r4jfZDqxuXBSjMGT1jUXnXOUkWCUrPZ7vjWsd7cXJpSvG5iwezbjBzYevbu0/u9Wztt1oO8MDbPFJU4Njc1sKQYA6aSIXqpNl6oZxjGu29tPHhwFBdmGYBtzdYb+UFTzXXw/QKCLdMXWy13M91BgagLHNHMxYLUDYMwSR632pU/ZPiKj3OfQ0E3IxLvklKFhkPlHa64EYaJPqy6knckop9NdaiSFr8GFrTbVm63EDFffuuOsUpgeao5LOv6070j24RvZ21ZSj66gIH6tpCrGnFDy/PrX/3SsXQ3ne+eZgFnEt3Rd48ePUS499xtaSDYQwXG3ao6VEZNoetEPm/Nefn6pTftMa97+wcPjg6+/uKJPrt3+PD+Krtze/uv339vqZgqFiKH4JH/jEGhDKjCFLmDHWvkdY9vEZuaVijlUGSENyjHcTtdXu8fEPaOecFpFrBxUVXWNmdLemtdddctq1hyScpUN7hEMDUliSmI2Bq/qWEcp/TUh2+0riApVbpcIQVPpIWVn1lAYhqT6KG0RckqNmXGPKrY/9wlQpt1KmU+phkKXaWrfSoJI220/vFMZllIsrV+dLhfw71toduVV1SReCz76M1rClZLr8ga8MwijFO3pca0gqebZsiDYUvYDaPd0F2gl1EyaHAloVa2LGxkoG3PvOrMkdnID4CaWSnydmYGhsUKnIT+VPOZYyFQDTkPlmJLXtsbSHhh6iTHDvGV2VQ9D6opMilManPzR2OaiOUduK/GRr1/ebbyjGhnpE2HW//h48eDw+MnTx7/8LRzGRsQxaK6bazBQYnCJL2L1on+o7/51X/33/8zHerREHy/dmrp+ds3Z28uBKJQ2zp/e2Ex1oJ00ZVoGxE+MbZe8sYDnaSLe//413/7wPr0oyMnKgu/7BFFEnWA4v2jI9mcchllNxrY+Nk/4ppRixknXRxkugguXsaWxZPhstQ+x4fEagUTjbEzmPl5cn5hAbDs/nDI6kMLMezGtqdx55ZN6HBmaAFdbCuAfg3Xp4kjTO52UoYTIVydKWLVz9cYxbj+aNPApVWLGoDHTSofn9OYSKzQoA1wv4Zoqth3mE7SUEUd+iV1CipWxQvGk64IN8XxamxVCSr31IhOjMVRsUpKsQx+M8ZpeZVPTz0liPRGgr96JTBUsApKWS5OB1OTgwyD7fI9JGQbpebi/YMn3a8lHSdAmYaofFkV1SPf+DBvdIFmh2/DbhTGthO9CLUPtKml6CJWa8x5hIwh/5jDlQp/3xdvzSOxgW3zxmIQA52CYTUhmS5wEPYqMJJPdp45J85arCtn8raLNdLXNh49fOS4XhujsYxtgG8DhrDN4opP2x+Zo+W23379jffe/+67P8kDPV5AZ8FKdMEh/aQPW+Z093buioLysth9Y61Lksz8Pd7coP1U79uvvvLqwtuGZ29zBfUfy0BgN1t3Lc5qEaUlUEUnmujR8M+yjrsNEIWyJYWLR8XNkSF+jFziG05OtE8D7XYwZiBSZaEkeuOlD89PTzbObgyuqMW2BT0E7tmjQzyyjKTx73hLIl0JcvRtKBmGS/WsxPR8tH6yNvKSokJgpbA8QRn5/yVhvEyAwEmVy0kx3GTqPXClcJPUo6oqq4QhMPAKziOuHJ3sPRUuVk7RB2IwQE5jqzgG8vGj9FWSegM5OJSzzCGO0uG1NH9uJ3Mc8K9rqvaoFpMlABHg8F3wC0bCTDXHnGTIeSsa2oNu+d0KnO1kMN57fHxkuR4NsVOSri4sUaHZq6gEGSzdnrwJXohbAEyxF+wGYaOUAlzO9Np5hzou1jw12mv21/FHUTismGkB54aceZ3mqG+ble2h835hx9W0/rJXAHt14svXJ86T5q8ixZKFqw5Kqo3o/MT33Pd//utf//4vf4yRLtvQGrDVu/ZK5SqyTrizqdiHuWnjWlCkf/iBDKqGEifZv393WCwRfRrgJbSFaDbty04+fWTDqtMfoIvZyaxLjf56TDFi4c/wIZ6OGiWJwPYrs9LX692JyDNWLB0OcGNahoovbK1Q4chsBlVhqvBQRX6jPrjnGqRi9fxaPpL0Z8UYfZC8SKZc0JhSn78ogar9D74nVTtwICsxVlQs1AeBARZA6Z8/KglqKPc1St0w12QLpv8xUAFVxYdpjeTUVVGFJI4q/xEKqitFZ2w17WOOZasl+FUaATLpcwzQagg+QURWt/IsLj9AgfOV3ucVwiTyagUljB/0GC3Bnq5Y3Q8p9L4JXAFqY1x1Gv2w2qdVavhfLal9X1Or2VzTxhGvxjavqqflQGOLso2O2VuzdnPx5sJay+sbb8UL2VCLcWE1tu2c09vX59L0803daBsX6dcHpaYYJdy3MXrs6qMRB2oDi+ZttXX2TxaNb3z95VcqLQxrSgrjM80UJTd9bXjOckg59cpnl0I8jSOFmMMXvWx9uDRjCIQaMoeVc3dtEcG21SBWlc4DH8zc6SUj52lJK5gTStiLW4ht0ypgXG4vcCHUlIU5f+S+aZhUInBJIKzc+GdgpPZoDPJmq1FOcYvGIbnKTkK+lXA7eC7AK14N1cTjJtcIWVSmalZcl6yUKyUbNcUKTxcMFxhLPRGjVB49n1dXYkAqS3G4GtC5iNmOH95QxpjJk916qkA1jbKj5/TsjaONdMYM2/um83gOJJJlmli76ZQpkg9zEwnh5E7UgarkAq2RbjhVh4QwHdVPd7uVAqf5TgzgLwiVtPwAYxJl1tpf2jn88ZMFzGwWgynix9ufDg4PsMXqf8bg/WjA1PQvLI1cEUWv+UB7rPeJMex8cGp8Zd4zdmGBzTunVl84xk23eeYTjOd2Pg17o0lDpSNnJhrnyHPyYNAjHauUCi3s4fDg6PjwyJrfSNUkWMEB//JP5Fwza1vIbXPJ+gayLOLvLRCEEtVXXi6y24CkSbcNltQuHp+IWlQVvyZE0pURg7wXGI2qCXeGZcHoTDtrzSE46k5yw2KIJqtFCCOJkVp4j7ebDmvPY9rAWRQj8Se+RZuj10OfoMLJ7WSm5Th5Yzbrk+Z4oSt6wqrMwSpj+ZfUMg0yACyqsbCqLGEqdYwp/zHAZwa3PAuMwAJPQwI/gEceqWO/PI0Drg3h6fnFe0uu311c7t8V9+dqZm7LwwJuOovMuokfP9m0/ubyPe2Xoohza2wm3t05NsPlQBDRs2k154pbkciATckaQW/MjGYlBNTlqwcHuEE3VOLgjBIPatE7GcuwQiBcRwMymilSq53nTvTT1Yid1WPGwMuYVFeTI4Kwf9ORdSDbQQYLTT77rCFj0rPfuiCglTIqnTBvhjEMM+HxT1wSFVov9D/93d/97i9/8XZJYYypbjNgxpIYDx9vKm1jy6Bt+BGMrgLjoYIO/Sh+8QJfAVKHNY3xzetRvHzG4Zaw1jJ8oKa1rfUr0sjmi2l1S07ApNPDKjmidhBb2zL/ZjjWJNan2R5ubl/WMKYQyMUe7cOGM7bac3zjOJkRN57GvyTbwfP37x2KqZokiydTHI6qGRaVDyQCmRDFeHkWFcrlXEkrgdaa+5nDq+pFSN3QTe1ZVE+thOdumZOvARnWD9fCSQGgQ6WCExWk6LXF87Qe21yyDQ04FGMUmn+Vr3LMXFWXXyqwURwm0MvFDeJj9lNhaBJaOHtW5XSnVZBXFFonT0xsB5YFAjhn80Ue3ILNlmG/F3mzh8vLdJ3IcUZPj/EQGOkymM01R3cZMLCn7FLVSA9D51A0BUZBWTLSpMeY0PQ/T5Z1jiLFiHAOw3KGXgZfAcWzCpAKUGMDOBgiNwS0r8LViBvXbvhfgPDB2Y1OA3j/0STgzu1bdGZ8S+39yNR3VSeuqUx1dJ2nTwXVMKwzWvRvf/s77xuQCCMnwTF7A5788rZJzEZCQavb4Msn3jGP3W39YAeb29zTAZJq0nVFDSBiavNaGmGxOl9B9WkI7WDe6rTtS0Er+biSKKxVXDdqBPm7d3dtk9rS2/j07Pl7J1VZy2rkKPGbq57WETc1LrjlBd1OitHoeBlUYeK018m6gR3sOj5s08n5W/NrpABz/2tWLJk2dWNO3nH3zkRkCIkRWFTGpQTXf9pR65l8k8SoUrJb1EvGUufX1Agrea1bU5lTmjAo2ly+AjEfow7/8DMBS6pShRLVqA44rMC/YKYvqlHd4DWZB+gCJgGOLUfaILD6HNSCOAYD094af/32rdkiiFoPfO/ekbfPa1ZV2urd3uzi7IY7FlkaBjHGJ/Bog0czQXW6WmvgCNvWBti89g5K1iCEV9sOqwe6PmkzhV2koIXA3UgLd4hl+oiLG5XJDKDtNtnEjbBGWAu3JJeAuBGNTKOdlStFb6QIkDoNSwzP905exmCcHpSUJG6n5eAEtsjbD8VdksNZAv0pdKsRUyhFahqY65535+XR0r90AAe8mDsDS6drAjHElAry+D5LgN6/v7xzbbWSCZDmzjjkO7t7FghqoOz0UIU2jppiwLgvGtbOh/tGpvf3vbcTl+1BYEUW0jqU4OnLl7MWdXPDyg1HIiuks60dKhgbk/YJcT9tYL15wEjmVPsObcfWYvQIXL853DfafVcr7yevhjx7Hr55/NXXT77oFcjrN//Tb3736vWraYDr58XgmBXXMDmlHE4lsHhaqhYCGelpMq1o0hr15QAaVSpqxkRvmqgX1XMObwr3kVQUTRiypeVSBoQfEqQPdfm/qYYIyi1n4lsgjBZVLEj/6dfAglPUj5ol60FYVq351oYlMdZKcEgzm6u7n793JqljTThytkfEqDElzC2dOKoWFes7Z+KqXpJ5ZX+zgVQ6w+namOK0KPl3tmvM8agonjrpHgxa80HYfSMrc+DpETEWsUI97sVzReff8EP5Amk0oLEOOOAjg2HA0oAsNhV3Fg6M4JaKI7ZqYv0sgpgcUgIzfGMk0sKL7gdUbr2FtV4bKT1hh1IHe0KDLJSlIZJoXQhPMOCJaMrgTtMEILWgMHwLexTpsu+Hae5cdEKHM7U6DI/aaIvMEGoZklRXlq0p0HRwoDVE19dnrotzw6T2Te948T1JiPgbxjJ9Tiif7YE6AmfBoCEnfGnfZrAAAGErSURBVBzpt5LWHOToTHrlxFhnP4rwvn708BfffmPfz5PHD3fMC99uft6wwKuTM7Gd5onSDT4JI7wgxtRi5Yr1aX9Y5/zowTD0ZlqhxMdr4FurMsLFGzjXbEkSPmIKWQxHBmqqHbLMJY3BvRHGRAExvgomfxndLWXTm3m4ABoNoEwgVqDPEevwIJ4m43QABUu50SIPrBZzvHHv9hM9OpPZKkkboewU29h6h75xhGYM2MOUJPXbxscLrclDtyDnHlcKF/f3C9LFJKSglZACQvozOHUPyIw1dzd4DGbTfJUEQcTHYogO3MwJdwNRqDhUTxlC9yRujB4jR/4hO3In4zQajVS6UYZCZpVLxcvXiGzFkPBZmcQiALjI1Zhk0Yrz3nqzQfZc0MGY/NHR5hZ6JUIc1mJQ6ZsbU6hnF2/4dIo3a+xEnh/s4WQWTrJnPNIfP3rw97/5rRXM1hTZzmlNwoc1yzeL1Lj4l6dnzkkwsqpqCNMQMf9oNYUyQXGzeeC9vG/FrnMwJTPFiV7vFxYFdteOaLcDXatE/68Y7JyROVoQJ7QMpnjXf/7FY0e9/eNf/erbr79tg+rebvxkss0Kbd29c2e1GiaJxDGcTYi1536kxIu4agzEWxg2F5cfHwynFrYpm0Tm4hoVLtydcTGCWQUtA0eLNcIbxUH12Ica5Uqdh8NhHo/jSe55OoieRNqiHXBEQ/rSp2r7QFSPV/qfZngW1goOcdbP37Iwxvlfjii8uTk82MNGekhl7u7tiI9UCjAuDHvA6qWNsVqXTk0kN6bQUJ+CIdM7lFr2Nt0wKXKFaLo9t0NU+QCLtrHb5WHMAjDfrF738doXsBqPuitYFSsCBJUylZ9hDqiEFapT35JtKT1PlWoQ5R8glq8BJnmwo/8T4Exq8CHRE6SSaE59zjTZ6PXMjIFTM7TAKYt2LLHju0GuzzDvdH3+8tWjB/fENiYCrArRVZhDXIQ94CHZO6OOf7O+7lh554lcvbdScEcXHwon5+d/+uH73/75z3ZCxu6I7AsiTPqWRb66DCzSpKAFeE4U47by87PeEHvkB52BElLvwS2MqwOeikMtbscT3Rfx7fH+8dnJua1MdGL0bdQ9mv2va0Izaa2Kx13EmWHUdKNXjKz9jG4fEJ3LTbf+lBijaSRWgpRsK55q5iZHaalO+uG2pyOIktE98FKUWgO/Fo7UBndVKBEVKkxChRbbWKk+xuVGQy3xJ28/F0ADTPr8TskGFqCwrtEZU6ysovULkRA9sRGSVahka9GH7RIrmKAi2bN8b1m6KgdPX0kiV+txIXF307ks9GM0Q3IF/DV2Uiy11FRGiWquufCdGZQ0pAGCpXTZEhspPJGHilKDfrYOcBk2kLGCVAg6skTNwOvbf+zqge+xlsgYf4hUozttF3N9bPrpZtP7c6w/P9p1upeppGX93yzMZjlOpFTrzbU9vWajnXYBV3mM0SF90CaU6PX+kfWt27//7vtXF289MvZqcREkX3hr0LvL4Qp8RayGbPpXy5a8Y2MRfxO6G1tPT1861cLCq00LW4azKhs5xPJY0AF1Lq7ranNt1r4kUS24qY0tHZF6H02rITyGL0zHbL9s7PB2gdeXb3PjHozwQyIBjEeJZyuxj4IlmoGQHJMgOqLCXT9VA8lIsaFn2DSiyLdNBY13ybmgUamlXpniGdB0wL8VfYGXPl6z+ymnXg1rMD4nfbYRCA3/4RS1SVe1RRaVDL+psA8pQaY80x0a5VDBymVOu6tMYqxZGoVTbFAYKPA00yNFarUMb6ojXBLgvILbboJWCbUCklfyqJdkq9j9gn11JMT62a4wyrEBSZqO3nA6bzP6FimIHFqivLXlWDZj/Oiz4EU6PADXRTbMIoapDfSesXTx5t7xsX5+SGXH1J9h1T57FM61maGfZGaKYyRkSFSwbNMFETbXpmJnnTw4sphn15IdsY7mXo0Rme6FvYMsHKfLKqwYNADNBA0kILwq6rVqHAxO3Pt//w//+g/ff6/BIR564u2VLRCy0lsGcfZci2y4Xo6+zoeNEOrBGt3lVyfn3v55vH/3/fs1L42g7qiFO64gwFb0FnPH5iIV65oScHQmRTe6KUJhW/pgIDqatNJpgvECXT/GxhtfbcajRJEVLVaBSf1LWn0CuWhCd7JRATnL7q6Yp9/abjE4XughiNmSAgGoavFMflK+6q+sCySMmKKgVgM8p8KeqcZHhhlSJVdpeH0uHwK1NgqS9+p7DIIQhhwVKTzPKwScrktA5qqp4VIzCU/9YX7PxvcHbkXooCbLmPS43mHWZ/ZghiPD9Byn5TRq4ExN/Fw6o71HkF/z6nYu94Nen6GLW60h6JzFD4cHXu36Dl56L63w6Vzahjf4YAxE/IaBUTTUarfaxQsjkUzhtSTj9UcShrzu3pFJTjjt54zaFxdnh1njPNnDcHpSEYOohS/zHVPweUa/Gyjil8uzdm0xHK9vZbQTKT600Mq2tAw2U9Ew9PKNy4u3ZqOPhBis0bylkGpzy2okVtpkM6v92ddfCp/OL98W90SPN6d93Lpiw239Gyk0B8IIdYkRoZa7dzlxBCcuVd5+8/6d03YPZoH4zY75oPhAXfgKc92chC5LHGcNNl/3LgkExA9kYZfeNou0u7XeTA+kd8Ui3m7rlt4I26apGBtfUkzMXP51Vvg0J9pBLFrcIx4pn+GMPlVSscZTIDycYl8f65BbvJ4ix/5Rd/BpVxyvflV1D9MkQYjIgMgMTSxKKAc8ZC9nuHf5psxTuaJ+TyY5fAdzARx26Jc/hpSvOxWnzf3yfNSAqKfGOsYehU9Y0aJVjQsOlZg6wnksJC1ZuFRGSdyYvKXVtUiWCmAfGeHNcGZt28tI6oTLYjV7rZZH9eNjSlELka4U+mZtZ/tgwcGxqCFcQ7FePBvzFxIkRy9Nmgwk2Bi/enVYPdAqkz4bGj4OuuHfFaru4tdQHJiSFsfqvnU6bNPagk9aoU+O4+bovDolWnqDsprWDKidUq3ra4PR7x48FCDR5K1bXpT2wVoPjDcLUDXXa8cHR0Ys/+1v/x5AGKhJyNCOv5mo8Xa29s607NcZNk7f2TSWrb/hyIKsRIOBLxbhvXr9+snxvTls3l7txUgiFhPEP0I6aloTlxPIntK2xVfP8X28i60S0+zqcKulceLIn1Xvx0dH0421DKSkFFxnugPWbzuJ7d6BdnHXCpE//vWvDgofcQ0nE4CrrwpUa4xstJdJYqOlLw3AUQmoybLkyo6TW7pUEa0rVBPFTc5jJFrzsfwDFfjwmnfgLlWW+BkaQLP0RobyyAyCh4j1jxJQwlGbBWSoDLpL/dBeFWMENQbTbahZCLvPdEWaqOazMkVwgqzKLnaOIuw2EbGX651G587u/sAuHwKhpKYtEtP1M4B77aUB+R2kxjvBQrYUAvTYTQKSlPesMin+wIgbHoR+vhXkHIgc0xqgeuAAIhkVEwvJUI8oM4tFA9ZHRFaj28k6P5A5Jzt1fortMnSAOlJroRdLsAT5veGjrU0n5/ppm+Xv//KX5yen/NLZ27eNMlmG0eDfHNJZKFarAvM07fbtf/JP/vG//8NvCTnkW0Q8R8temfXvNFjHScDQqNH5m3ONydMZ7RA95UVgL8TXSfjxxx8sMNy5d5t16kYnImsHOomNw+kU1YYvgUdaglkkFZGyeYWGt8S97tBfRk5NPt1sOBcj746Ndpd8+eSxxQImLJ2uxOpub/UC6oO9HafWSHXWL6lYk+hAjpcOggdfybg20q3SWIm/vlIHytby/GzS3sPiyObOE8TIcUorkKRCFBKDcGY5ssGmUUOpSYgSlD7uc0VglFZr9XY3BoDUKZeqZAS1sC7tUUqB6dW1+qeuijW0NJpRmaXOftOVlXLMDMGACfdMKJxdy+eCQH3UyZ/GxxiKYAElwtPSUqjCmBHYdUKrFdU+02Bf6ftgC2yJKy33BE+Gp8DkLTJyWjEcqbkzzCPwMMg4Z7WrKkIWLIMNsooaAqqaYkJLLVqaAQ7H/NlahpryZng+KN8vv/3W8fGasjeXbzl7jfuJHWRbr26/faMWI0mCQKOaF0Lz9++L0rY2qVcHS5ucWb9lTjCem6b07qB1J6dqJZxBv/bLn//i4O7+K2fB4wxEk4xtelcX1+f6GOkkMoVDdYFgas/01an5hOjSGnl1z+HBX/7ynREkzlvcOOxKbmwLnerQKLvYl47MRE12EiEV11IXl07z6evX7GX61ptbloUAkxmJ8651QkRqh3f3/uk/+pUzkK3lZglwFFbVedPoX33c3bllRuJ3f/zzx8S9KER+KdanVo3Y+FtvBl1K0WFrLpJA/iwikxA5Gqzwm/pkPTTFV79lSYcW9R2ppHFh74dSo935y8k/sh3aKpkEh1kBS2cpVNbKGwGxamZS3zAvAF6uyeaWjufS6WsUVN2iwaOWS0NQ6gI86kMYpLlWT8CuNFqrcyDLlkongqU9obuVSrtjYnj7FTqhuVwe1KcqW8SXRytdndM/WajJuJfRJupRbdpgX+GADKUUHw6F9fiFZIJJ6cQEnz0ojlKpvNire0c3/GRbFPHhHOPlAHuqVeO+fnN+eXlukKdREH6mnoA1V/RJiK9GLTHlYjB2MnKmPLrDva3Pt11Gc4IQusc/isO/fPLk6b9/YSVGVk1d4ohpY0gUqqjKhieHpiyH1qcgnDUGUg2XhV4KXbxzuNM7y0rqoQvvWwQMSnMCQpBeaHDHgovknt4M4XgTczqaRl9ly5DwaIVS4+A8dRlhuHv3njPz7+weHx44KMDs224HOcbLhAHFutPr+5Zt1P7U9lVuCifl7gPoflEhrVnq7uxEs5XVNkIfu5Fcim5xoxzsB6pZy3JFbf3pRWel0biRU/mLd/SeEpssOcTJsMCWMmo3PAkVHFaXQj7hlZqkMYUNKlkEEN4hlyuq4RrElnsgTHbO8wgAECzxflD6OUkVWEYtpZKZqkQjaVhXrBnk8nLZSQihrY88tTKVnzp4hOxwQQueUTgmU0VepPuJsLWKZS6/jo1ldm8B00PVUW6N8WCkay7g1p9zaKkpPx667NXHFEJvcoVDG1jCpEdsAFf9QyPgOqU/PHsqiKdvec/hzyxNHHQ1ACbqvQTaoLNLcQNfxOOQ2dlLzL+ylju95ufS2gnjUFvbOzdt6Islj+4/wAfsWWSAVW6qtc5yLm+R61JTGVlmuoi9Bn+sjNvcZJQGqg4OdMs46k94IJ8lfpqCNyKnfSc0HlCvwgCqkkhwIIpxHL+M4KoezbWOKh4vgQt8twWxdrcpai2NYCwD7wwPA2YN7UHDI+0wDbqzs/3+zTvmmUwhnfq7TSWpBLhJWjumlB/zXgyNFbMIl7SxbpyCKcEguYi/9gKYyiyyCp4LqAFZNUmMEseU/i2Xpi9YMq1QrcDkpZU1L2lkg6klp3sUwl1tRU6y3ynwQAjFSmANwdSylTIK2neCwz1iLtdPmaeJoyx85SJCapwj6O3zggjTqMlBXWb1iTG5N3+3poU3ZGLYDsdqGOOnCzcHOnhVX0H9vxevzndvW43TYAn0MNjOlTdvDDdd2xc5Q6uVFRaYqMUljf7p2fnRxgFFxIBV81EWl4oAJkxG4sKKvgvJSsp0nJT+3fOnudqlRNnKw4m4fLVLhZ9Ya3GeXkQ41cR38A9yGprVFX5nUVZLKmqnxuWpiKYc7JnXohGZvRTUj4XKlCOtniqtOoFkwtC5WpKkGwQF69QRUw0wWfhqtXMvUEGy7ov2y/ycubon9x9GjMhxNC9gqV/ao0NuAS/NzuihlT/uoKVy9NKdzeOj+0+ffe8phGLJdNZ5dLcN6QKSyhhHojXgpbKpWjIMgqpGi3lDbUjObZ5cv3n/1ubtaT6rWcb+KSx31Yw9KDz3mX9jOMRPv5dqBjB2pHCp/0QKVfbTxZaWX9E6FSxl4jtE4J5k1FQhtadhczsJNTV+Z04DxVMAawXjsIfOlWoZRZBAF12E9BAMVJB0+9aevXhN8HwKGe/sbNnZrPipIFpiDq/Nu5rbB/cPUpRrZ7B6W9QlM9idXd6xYtwE1QjjlKFi/qHNG9F1LHfnNLuldhJ/9vzlzOnesovg5auzJw8P1ej8Zurh0A2K/vzlawuljr2NKokP1TkgVtQVBVVTDRJLViG/gss364KiKOxBo7RljkFxL1patW63AWUg5AbEwjRUP706P2OiBvXZPN3BLQ1CMs596K5U3IVRLA74KouvEFjgg6cp7l/6tWLEzKwxUsw1WOTQcL1VB/TeO7wHPcC9qUGs+PSVqbqL184JvH2mfdDXgRmKqBP8EKG4ANH4iVXH52deyzWG1PkINVtqHuVcf/Lw4V/+/EdHR93Z2fu00bbd29cGhrG3F+rY/oH4186uYSEgmm3RmA1VYYu1KJroNHDIGl1DCTOwzUO3RHCOMk4GOtUY4D7iwwKHYdUnKUVpngkOSWsu6TmMFK8s0tUSGA33WNOChjoGASBnZKwKAl9oMqDIQkcsu8pa5c3BepQFLyFlgJK2UP3E62Wvrr585AR2mSfX1BsG8XexwF7Ip8nUqG7vcKNknGnpshnafnT/MHatbXjr2Om5Y8KI8fb5m3dPn1+00AzQAKdz0axcXyEkIYwLs2zH8briHU30pFvZtQZC01G2R46X1PjY6GsNlSM8jw7v0jsORREHWZuQbj5WbAFySlcridLIR3pml570ED+7KdxHH28bLbVIo+VDK1LEeToGBwdHRiuFKLV6hgeHP8pbxagtMptkOSxB29wjWhO9c9fspGPyHAJk6lo72di82d6kQ5PUsvCAUKWI/1GBKbkkyEAvLLOSTauDOMynJ68//P53YjTFnJP5oTM4YqM852/e6gZUVaCv7ChFhLFc7NMoqNd6jYv1CzYvM+XeuZOXTTGx5+bKed+QtRDKOOCox82HzweNIcN6rJcvX55fnCe1go14lMIMQ/ERlxl6opJc+ejhCazjMijmiNeVdCW2E33aoiJsryRZNQIorQjkygNi3wiT2Gc1JDYfPesrsUrxG5y+5kqdKijkMbLnR8+wxF0OQh4smfnp8UfcvyQZRvNgX2UZl9PXTs7tULM2+2oZEAdJRngmorG5iFXS7yoqOPHSAEv7TPfmPWYYtHH3G0e/1wsHWTlK/PihtQZn4RtlU7/yQ0ZuRlooB3tW3Deh69hHGuJAHU/NK99xqhdNbq4Xb9cNaJo3Umn2OXJR3QIjzMKb3D1o9eT06VtyS3c/s0cvIFrUTNoO0ptheXmLEgWEzfgtWgulj5+eP39BrmBSRHlyfRW+Ie1nL17enncCzRFJzmt6L6SDE/Sgof/AaJsxzArpkf1cY6a0KmTiZKNbdCO0k7GvLAhm9ai9k+TunlOJLz58PPvxKYtSjmtLJFPaN9z1buRXgxk0a0QgKsPYEo2zFn87OrkvIX+r8HF+Ivuc+9q+M13v3P3rs2eH+3tH3ozo/MN35h/qEqFQUPv7P//Z7CCUYIbbgYUiKOWIF1CfOG+0GQnpOSm0XFHjPuq5WMjoMox1gmORuwwn1YZfYKfcMjMV9BAIVU/nUSmxKKHXbvQ7DqILHn3OBcokjvZXJI5xPpK5AABl4Ol4o4K3qVVFC0OVJC0LXIyZV/+CUhgy76kwZEIHze0f2doUoFIRPqvzRJcx6S070VNOGHFSHhEvXmv7d2+vn4otPaANgc8ggE+g1YU0x+47Y8FLKd96fHLGhdkvBumOxZYtAaDFAUKkYZFoxtolWeOKLcvRoKMOYwOqabxVlDt8agSt6iPA0mZ186E5/vEXVH/OPAVQn5tVmN4CWP5RN5mjXwuPIdot/1wsxadj8+zogI8ACTVDCC3UAm6IlP/w3fd/+Ot3yaBubM4fC2GV8ojDRpqZzViCBybUobcVYIGQBzdr3hlkpd0bk3wj7EViiTadiHcWomiC9RHQJ96WVLs25Do7LK3vWnfyhNXi0J75/xpEANCoC2SJ3m9+94f7B4fbmztFcldeDWSfzbWo8T/8/vffvXwp1LEnaCKYlignv1GSVHmuxTRx1820azGOLvjR+ENCCDtIKRvasUFiPFkglGH0O5Vt50dCjcdjeBkXZaWN2V0lVBBHpYKwksln1Q9m1Uh3jZhyK6rP8nq6LC2ueLkWFOQbUCZ9RTiaclVM5oBprYGaprzuVCY8U5APeplNEQV0rKL3Jo29/V29hfNzOz/f8QWiiAf3981VAVUQ6CSRWm7Uea9MXCL+wfInfGs3zVRpWe4d3V28oT0VDj61nUiI61wvj2q+UstmYLvp+AkEkKc3c7LhOrJ+jNXHiij1v+cLa9KmJYyQCk/+2DCoOYRLQ59xQj6Ex0Llh5dE0Z/7ZrBLTYVoPU0mXa3Tydkb7d72diw3+mQgVpfp9cWbZy9f6s16A3jBfZyk2YyaMPP1C/tT0uF0nWHK1tSbkVISHyS4HK+3qNW4eT9ZRz1aQw99fGRjMKu3DhzsxwTwIXL9wmb1aN8MH+nLsxbepS6//q8zDuispuvGyZv7lP67p09BN+5rXAMaz0+fv37z5o/ffR/NowewTjlWiqyWAMSQYXRiHgSGWXVWLeeKtAhNxVzgx81gdBOI8FwWomZpwtiYNYxeKBqVawIlKCqapiMuDL1gLum009PR9YQ3YszYqpkBTCsVEsNVSeoFYrGqwSE4MOLJPAGLDwal1HEZaVZsWCDmmGvJBcWtcqMbLuPqV++vPohe9ncNqXtRkncBemmnMwG8ayuwELr+WK9x5pVjTHpZwOllGvTfiiOabxJaD8Rg1ZWDeqiZUpTMYgLDgDa+NEi/ZrOEXsQlamzdJETo2uTlBFVGIggx1kTL8Kr5ier1L8Zzlhb/o9v5vihVb/xYrKrtqeIGLZKBenRuCIxnGZJCsSEgMTBvopQkuXRNJ3DZpLaKv7Dy+f1l7svKWYfGb+klRuO7D0aTBD91DxZ8BtzoxLQwEj0ANzNrKCjFVhHmqo1aN/vQu5Q7+AjSWfnQ86kgpgG7lMorHsxR11Iy7RaKfARu6ARtiSJ6X87l23PYWh9rDmQ5TBOvonBt7dHD+yYpfnz98vzyjcBUoGvU+K01Zd6wuyCOslCKkPiggimaN0F1rrqEelrZXmRpUM3Al3GxzkRe70K6VqXSUoajnZWQRnQev5ti+qXTJIt2G4CMpXgPa+pPU8EZOZ3GJ5bFbOuB7SFWr38ypAdJfpjmO3mr0+BcwWlxdiNjxm/i/1DlcZQ0JlG3EgP9ZXFLR6J21rh+8ZTyMPcTZhRr22KhxMx9KA5ZMI1SMN51e0Pprhkd8kiTmurqIr7h6IK79mft+x9ewujRAyFqW+bVq/4zp9LrdPaO0A5TU6/TfV6ffDh5bYvVLXg6kiym3azZnHjx9s33Pz7HCOcHb283WRbFORoePJENsxVyYRC+ypvzXbKplL6aKGiXWo8mIkpMZIi7ZQYHGJYMPaFh3d/CHKBSuY/XnxxpfHN5UYH022DPOmRYV/UQXIx3VaHAuRjPVVMmDT9TYVUXFIR4YFqVPVUnfWNCdtw6njplG5ISAbeRAgWdW7ZvyEvQvFk6IowObds0bUcFjzK4e1Orndc81rt3t/ZmC7ZFMpFGsZRYv3/vgXdmvTw/u/xkBXlNto7lrHHQ8OUypKFabcDLgIZu4NhHrlcGN9IR6xrl8i4ju+HyJ/5GDErKB4iCtIZfy5n5aa1YliZ2rq3PgYdW2eXmhaqnUhSXz6BiND5FfU/NApSSCf+cQnnJevb3vafVIXzhROf4V9vc9xqSB1Cr6LtKDfmpyfGBUoORoeVCqrepj2VN9Tyk8hubl5efnN7jJNj79w+iUTfx09WLlyfHh/ajm7Gxpb1FZGMo7Tyws95IiOMigVVvNIsWzi/F30b9Ntfvziqy+Oe/rQcL7XG22Zvds43LH5++bhFbr2PavHcgUsrGbUB/8fzVu3eWHSDU6rzcgBEmB6YIoRDRYYjYmO0VQgOeuqCa8jQ01MHaCASWrAQ6VDLboEXn55YY1aUoK46GCeRGmn1VwqdvykAAPK8Aa1LIvZqGljjJJUTUR8eCmKqy69VIE1aK7uwRx+4BO40RgeHO0qkibiXzM2a0TE2bT5hLAkp0He7t7zNZobNkAQ0jAojzXrgAHZuVjdwd7Oxip3Z02+GsBZSRUtTZlsVenCp43dvd53s8hT+GeKQ9vnNn7/7xEUtATLC1JLMkznhabJTTl2qazpxL9YtVLo9gyRcymVGpOjeNUd2Y/K4QMVDcWNpNReNE3x4h3C8535uJNNOxuWGI0B3AFeByDHRMf7Kmo2kv6mArfReolp2P2XUsmr0ioPDNlorMy0EFJHPYrZKtiLb50Fx7M7K6tZpZvk37mbRHhjPiEl5v3hFfu3O9WO5wbxciY1Tm8j9enL9b2+il3AQGeVol8nz24pWllzzf/XsH3t8RD4axohe05J617Umss9IcIqSVsChLW1ITiv7i7CYi9AVIhBpRM2tXju/duXdkFzvHENGGKBp+8NLBW5uPHhxJlkgZVwy9ubIoxl+lQRl2uwEcNq5yE91oVIkjlKmu5AUNlqud7CGtCN8CisUq9LInU7xqsInHS3CL++oJbuBJ1ORpcma5xIQh1uaZb1l/YfBAVjYjDzh6Yry5QKZaWjhB7b1cx4vgqYV9myhzyusQ48Nvo8n3Dvct9kgeEJNdz4BS0j1otzx2nS80A+/YJ5iCr6qmokfC+ZhGczBo/ezNm3vtxBMgcYcCGCR4zNg2vnryxW//8l18iFkNdOQOZga1GvPfHi0X+cVexJME4lWR6oZNXaCp1qeuvC5jkOIq1isTg/ohD55VybTFVnWBGBCnVqWGRiSdIuGEhQ0jM3hueMvpQyneMj1y/tYtlAI+wlY9F4vlaoE1LpvXpbIiX9NYtzdbwe6nejmyD2sMRmlSWfQAfUimXNq9Ju8haezcOjPvmDX2IZNaeJO9uzuNuhspn+6B6h1GoqswwvU2GptG0EGRaqtNqK3kBUk1mAHY3vnmy0cTHGreFkmCXYfEhAOvWk2ByGXsNFBUdFBC6hmzJAlMhMtyoiUGZjwpb+ZTWiAqNXfuUYkpg1KGBxwXvLCa/Ja6StTlNcsUmhnP6LhiyvnLFYWEBOBy3H6gMd2t9vK5KWSIwzVH68RgtNKmN2Nx2kxmr0vjqGxuRidIBjAbNCqiFk3YnPBetVLb7BX4Nqt0X2cn8I1rWn2ky2uPnCYnXxmGaK26sG4098Pp2dnVo0eQyNLoX6xjyfDMBhQwfGHJBkfFToyTtgkwMo3tsJz1Lx4/kUdjEaXB1oBqBoZ2jwuwY5c6sR77pvaFHMqfMKK/PdqWHsQu3DIOKOrJ/CEaiyKIxHy78nx+FzVUi6rrrtVMl7UtfzaMd0SN/sYnK64ApXYMXveSGVilqzMKxKJSMWStWU+D4sonzkFDlVyTplYiB4Q5KuP6TPIY6BRDFksY9ROFiXY/2Ifu4Ns7+/u10QgBfLFVSmOE9IBlvrmIbwhO2/SYN/VrIckHqCGFmurxHDKyFT/Ue4hX9G/R+ziaao8OyXG1dvL69P7xAbvzK9DKDNPmBrAEiWdRMcPZ7qtrBIxSkMNzwMo5aqto8k3XOULaNY9hEeKVLeNk6Cfe8KdTNOoS4ZLDLyUoTT4smFMJEEGZvyLdoWSei2ymPkB4E67eJgRdYCvn+BD11QJyGUp0ikw79fG2vofgki2JoHh5dDaw2bqj7tkMfsmjkbVITusZ6qjrWZL3jSKtrCOMCFVJ3FEHlVKKKvc5fl5mk9DXV2fFaQ77fucd1HUqwAjg+ob5Nec1vHt9Fn+GolF99SzxVVYef3oYYxSsqnqeE36F7RRMyLIBYdtHoWEZITtyLX3KoVnBRYQS4Uk7Bfe8BR/MnSsAOlw91TCKK1QnxSWwMVhpfopDqa5oqALPsX2msy3T3RQBpuOzV5sXNOfqqUHqIBRYAtxOMUh4ZZRErIM7aHVVhs3pTOwcNVw3h/XBIgoH83ubsBxDflAwvXIt5ySQcIxqQQTVCQ68Yo7PeNVwQFmqqU9ktmvk0GH0YvvpPgHTs7JR/ciebLWZVeDBPHcnPQcPln+Ny42XkUoX5fVswq1KDMzAhpuMGKv46HiBegrFS3oqbVrBIXzIT4UAg2moVHtVdxf5Km4AsTapy62PWhuvtOVseil4uxpsKLAHgQTMUL29aHpK5iLSIZPGssXAz/4+blqgeXx00KkA1RgZWG4BzIbukU4z+tQ3DzMj73d6fP/Bk/sPeGAGpYNCdTCcqW3v2oeguY32EG5R6o5RMaOlliHVt9VVQFJOKx0zp398sP/01esJfQjQE+UUriyR8nWJ3M8QCKz0vquiGgBJJNOu6oiLd6zKEqUQs5+1ZhWlIApOJRIq1wIBYc8dQya9s9qLnA2tFDjBS6uqid3dcKya19zp96w5bWVa1Bo062Nj0lQ/CtdruJwxReEaCrSrabROTrEWBqlg+9ZuLB0H6k2BdCuP1A7jpJnjILnmodKR8ZsLcVEq+trY3AU4RVqaokUp4sTCheFHv2JcelF7kMNGy7iPONC/CB9H3reyN3d2zYfmyNLPsWpfi3aVfSInT8NmJBrdsa8f4y/CGP8LR+mHCS0ERGkyKVe6O/kDlwj8CMPgILwJgaYpMGIKVueKt4Gp6AJqCkGSDiiiMsa2AlW9qqsif8SESToJQFkVoi+uBws9DwsDM/u0JHrsuVcQ9yF1c/PVkwe//PqbLx88oPM2pgUMKqFgz97mpq6CSQQb/WyFdiLmwZ2de0f7D+8dP7p/n6k8f/Xi7E2DEvGyNz17nw+F4GwUD0+16x7o3rF7zQJ86yp43F5Qh8ClpJbx/eZPfxmXEXYoTf3d1S2pASw1lqZ8U0KaH9L9j38jYw+7JwCd1AQDtlLRPoT2I71wuha+gzUC9kJsc/JZyLSCs4BenvY93l7p83BkaaN1Q9WBCsSqPjhuZrIifBO+C/HJa0K5AhH5y6yKjDZiCENStjD9PEDKXeAx5KOrEpErM0HtNITAlqWUtSvZL11qdQ57+qoVdIEDEkuQb5w3e1tqpBBonOZhpZGhGgK0KQbx2lVQv4uOdqZvo+Zp0ngclbBYY/ZkaISg/qiAb6NjGDWYCLTnxNBSkgnHYbIy8zOeVBckQ34lwuw7T+fh4J5GVwKdfstuTU7K3/1I2sPyxIcl71Djp8exnmF9Wo5CrKXjTF1AVKFSeUZ2ImqTLDqtNs5dGW3HwyNHC9sg0KtDrJDLTgZ1h7dtPvSeBO/TvrX5zRePnhw/9CaRo3tesGCbjW3gXtbrdQ/WIs3sWSe/4CiHdMWPhaghF2sBdhxK7DSyDrhVWe3GtniJ746/+vUaI2HY23cf0pnEgkJFoyztkJTMSowzfU1UMCTF7jLwbXcO795tOaB3VO7uKZhAh931W35i/Cg9DWRlo8WYBWoeMcwJqcgi3o2edIMbPRrhkBkElKAecstb3YvdZhMNtwIy6o6GApWIKMMShcsSif1LLsp+1mzEz9ag4v4lFlezfC7Rh+ams/TmR3g22ApNFEIpmaoNKc2jhZJ0I06sSzq/8+H9W05tOtadXwp5HR4158CcM7Zt9nN8zvUnB+zR7byEM/Z27lhDIOQW1MmAPmYrrmsjTchPVSrAM23iOiVpVCrzg1q+plx+h8/yP32O/Bgqrf8t+Kc+eVIAx0MtZQNCgccnRKf/yb9aAxDblA94T5NlKI1mBHoZsYoz4xHg5Zb+u5lCstda+kknp5v38c35G/1o94oY7BNUADotj2rX7JXZPdq/Q311wg+sjvCazx1voTNnYInXR4vnrNrW/uj+4uXWlfc+FGFn5Qla7bi0ib8vXr2wUHHr6GBGFW81tNKxHBquTztb24+PH/7x++9TL5o2LJrKC3vSpVgXwRE/zjj60b3SuOLLrx8++ubLJ4YLSKtQJUeTP0vlKpdGDNdGEhN71s8Ak2eO6VmcemRfuF9XPUNK8bFGZsjQOmYTWqHUymd6RnKyhl/gInvEWp1VjoRwDfseTSU9yAmPJaQcrZXyhqPUthGdQqeabUPj+BqIHPz5+Ryl2oKaDSMhoJEixM30U1bxcCZSGNDZREbCMFns6hwHa0uNfaHUdll9d+8mEgXGHC7hs5jSIhUu+GqqqtxXvUk3KU7xT9tOumHxVujUHXZItVfWuyiZiVTsgNewI2qRCXu/63P7Iha1pLK5PbA3HPElmo1HuAybeA6nGByYYVS/k/tn8ZQ+VSwS7adyubdhcjDwkbUbh4Bt1ul/UovhjN9DTJxgWD8LXUbGHRtjG4zMutb26Ts0L2hqUCbPgNeH3rP77Fmk87gNhxfaQhs/uRNN5MzJA2gIpvfYNm44h30PtmHpqPG3H947tMP4t0l9GfJH5MBudGs2Nx8c3/vL0x+JE8Ype04wut2hP4xWSq+Xh+CIgmGfwz+T6UK3gzt3Ym5PXDkJ5kmkZN7o0ihwa1qHQL9lLBSoqjx8gvA6zwSW2i2mnCDTzg40CJn1Vo+TEjLja7W0AnXBUtXFSkuUsWgARCSNl8OHqVo9MoVhTrznOTJpXEmiktYEaqd8cscT59R/cCORnZj4Mc9L7cLNv1nPHC153GpNh4PZanbiU9af5LQskWSoJFsQ52dIC+6NFGKx0fURwYBKk0pO30ke1FTYG+7uOAZiNPvm5qBB2JLZbu7WHZLq2qV/YVdM1daL0PW7Mbpw9j9+Go/rzWC9G0kajmQzmSdaBlcZfccSSSgo2RXHQJFShlJjeylL5NfSErrqfACuljFI90l1m2fYtPq1noM5hJlJQnVVS3x1evLVw4etjKCgw9DQhihSgDOj/vTHp/nZ5D5tcXFVDTEf3DCrAXDvu/340VCSislPRhgl1GSsWd8yp/Pq7JW18taf2mInUAMAjlZGOFGGFbUjyXDNLcO4hL1M74roF06Q4lC4RPnDD7gtbIjB0ltM74JgDKmXYJRIHtXMrzL1lxcfKciYwKAqw8JARySURaZOIMTrNCiD9RJSJoQhmMAhNp8Gz1SL2IoPKjXoSAczDZjgdySsICni6IArnpE9XRy5epC3hTb8FklnKGFWvwExyk+cabk1eZOx54ZWPTFFoByNpXb8MchDI+XbONg0xxxaYGnX3WU7DnS5wxmlVdC3irU8KWvGUqUU2q9BRR48zUASpm/ULjo5eKIfylldFu12DNXvhFDe0iomI9OIPDrV5yxloLgF05pVA+jDikEkpmZBqTUQYRfA1bfSw6HcWbT9wwVyWDcPBmEa72LHvoXxjuCfI8yQ2RRyXmad4tLQMBAIdTot8956bhL963eO4tIezDwjRa+ZaJE2kh7eu/+bjT+oJsdhDF8UFT7YU1RlRMhyP30Ab0W9/UEM1bYE2qBpjYhhOXyQ8Kfvf9Aaf/3FV05Uu31n5/WJMfq3P7549sJbP9968fWg9W42YUS6OtJ2SC9kf+ZtLg0y3DwkUoFyxhe88yi+t4pdkgM8EsJKiG4TRQ2FD2XKMhnAT3rpJ6oV8iRk0ojGdngpaeWishjwYQQjBWdlGXVEZ0D6H6LV7JoumbRamJLUmny595S93FXRhYgii/xrtQnHYeOPPCMxLbZtkpevxjyu7l4zCZE8PACjwVxwJA5AQDlgTIyQaUKqSApUUthRMqYcJ9LmrC4cBzGAIRNegA3AhaZSSHUUo5yjgSGqXBrcXw4I/DxpP4I6qdJjZnKoBRuAvSDHQOcbb/2oupinkIyJNeBFiYCz82VlkmcKlgfQySxnrTjmVXA8uLGE2ZmgwcFVXLOIHEUiENB0cXFtTo+EWOedIccgC29z9sYWkdPNtX25s+z29/WvFgq7veCNcmtPuPYYX5i42AJe2RxGavrBba55d8urF9qQgVUcVgzwb9qp/aP7/+Nvfv/67fs/PXtZGHZ9xX5AgzGvMJTFMdWOS8CJRJ7I8Ca2yRgjXfMd4LClNaOyVvZq7jIAv0sLVqXA8zOvD6mA0Q7z9hJHHhP+DgOHs8GUUd00bbn3cKBN7eNNYZLIasZzfg0CrmQfxiOpfGCYFv/Iknh6BNU1a5uT94RUBJj4OKCI5a9mIDUayw84zZ6Sbv3udvhQPyjM48Jo9ihrhQDE1cE1nyUujA8CuBhaJdBw5Uswuu9JCQGl+ynTSteo8kghdMEYaSqSfkpRy6QoBouYVgVVUfGBvMifhXiS0kn0HBFhEjGAWvJs7ZlTjGY6JWMYplK8ejimwO1tPD68Z8n17/783b/7ze8q6w8NEFqBWXFBNVM+GGrkQ2isfm3TC8VDGh9VO2u4crkYh3JPV3VwkWYv2uXTl68t4zIEizw0xmh0+g91/SFnEVkqAw7FbOyvkSGEpGtskU1bkWuKzpqcd73rpQ3UpCp7Yc28g9HB8XZ8nL39cPrmBXzrXo1DJV19RZz1s3YfzGTfv9EV3EpqskshmJSycCIJL5eSWCPKEk/Af5ie13RInwCXm0x3FgnJSgMztXgiUlQiu/V7stCdVGJEya5i7GdhJ+YQxv0wCc2K9WOsNfUIQwmxrjt2CGzaOjl7XlUxVxYQ4DH9DVap7QW8f8VWgIwXD6hrNFtJ/7RUoZogvPVDmfIucKt1royBnqR8ZV+AKZIh+QOmC5EDSHqgB2nqHj3KRMcAC1N/fvspKSS6ot5vdzjjBi3B7qss0PeM9VVjEOJ61jTQJeYAYuGariNNf3ny0pvtD/Z7casHTs492jfpeveLh/eNBDg7VO/f1rE//PkvF45nrfr41Rdch3PqgPNUHIfEQH1enS8buz2pI5SIJKfdDCIUPhOFaWzFEVt/+v5H2tXIWqbQrFsEpXZVtnG0f2iwQsloAxUIFbmNpbb/79r9r6hhfFPbXpKlwzCBWifZL1jfd57R3b0f3r6aMB1HgkRNhVPrW7s6TdzhovqZ0FQagcCPXBvu84/wcXSI9jTxDDHKWvRhPFv4kI3B7pM+kyi3Vi60B+dCpyDiRg4tlzQKUEL/KGkCZwDpHiASh8CFXAkoXuhf5JDP8JsqVQV1ymOPOWNiGKNA2YFaDbJM542WqCpdkZq1dQ+V1CMMGkXNIAppxGN6UDMbLfdySa5sVYx408WpSfYZsfBwhsQglwCzd7WvskxDpMDK4VfngF3wzBiCvaT23WOsW6QRm0ap5ZGzexl+yl3URCxpTtZaevDmZ/nBCdSUghVWW/X9+MHDP/z5u4dHx188vGeLhT4te3h4/FhRWlOI7nz1m42fPX7sYLi//8tfq8AFg3Q6SuEy/M22lqeJSY/EYFnDohvswbYHjxo1miV3Rm5N/1cyo8ITi8+FKp9e2vXz9t3WrOynEL0jEWz6QMpMhBZbMsRNIjtSKFrdKSMb2YxBhgKk2dMsVHDAArZXpfnmYHTZWf7g6N5fn76Ef9Er2RqmKHJheMb+4hXDUK0+uvaHkNWbbcTvhgIMa9NS6ZD3MMTcj6Bww/q5t+8NLFqlHJ+xGBxyKP9nDQIK7il8CICTuPz3rZIMaH7WVc2nLwqgYQn/VBK2RVtdMKu5U9VoSOUqXKFUMObJmaiqK6XASSjrO9HNvE3ZpzqYLJpcoZIrNbWnwNzo4Hsd03JEjSv8lGcIqa4FV8LhgDyFl8pzYwHr+ZT6ybD9XrR7sb1+DAxFS4m9ZgkgUSsB/rBmoCy1L7cDeWCmSVg0pI6ZJoOpO9BLUzjWkPSGdHD8CQPsEH7y6KHBWcz1slE3pvDNNskHSJnJosNIrWPf+tmXX/7mT9+N/KJNDSPeURI4ff6W2Q9RN+dlSIhehWoIaiUELlwIGDFZF8L6JDfoZTL6b1TOqXpOVnIGd8d2QxJzsCF1vL6yHF+8xRIYoDAkM8u9aTv47wIkA9gzPyKpKUebJ5x1nGaryPkZTqjc2vz6yZP/8T/+FokIaKtRU875O5nMQwdQL8fWgpl0IwBFb0/zigjc5E0ZXh27RbIpCHZjSCyz98/pUdsPH+DbuFxZuZwYMAJLF+CDs3LnkmNLOkTdPNPCJanJmwIUmyVNGUyQiLI4UFmlFctVpft5PG0zHkmsEcpAghpicoKFMAKT8lkvU+/S6rp4KjlpU8XgDedxIlSmptHYtCZbzZzydhXwF7qBorAVCF6mXuJyTb5V9tgQSHwYvqgJEUOsRJwJK3/xYVrsqUUlY1WKLTVU8/LEo8Vih4oyxlm6Wd6wwzJfYwFjaRADY5rc5bapW8Zw73DPrC4SuFQ+1UBnujDUTQDbYBO6aMrXX3whWOKSp4IahM9IwWpBPArCda7qyq1HuGtYFPrF4cxgy0aaJZI0prNBv3hbWZFhNkCnszcx80AL7Haiyb6xbkrNTfISAbPEtGXAK6nxsjrMTEGjtKbiGUOriwRU1snftrDeuNXaxuP79/V7HNNxRVsWNbLvjU6yXd+pllTw29WxCPV9y/viWvxDQZzvkjKamEa6q4HcWHt9dvLg3hH6FuGxSRMUw8+RTb2LlA9TFEHIiInc8rxVMLASwNgazo7QcVUFndo9SpqQ0w2yarmhpU1gLupb45ku+LmIorrcSwRDFb4z3dGPaKrcYOE8NybU2U4pUNWNXkbbELv6zcq2enFe2hvE4XwVVqx//XlUfZWVJQOeOsCcm9VHlgfcoDWoNHzsZqgLtUCNrIPaVS3LNT/mF7wkAo2mJdNS8wAfgMp5qlyqPHyL3Z/hWPtoemrD8t76tToAjbVxCOs7d9pmBHks5U4LPdrdcmVPGEu4vJgTjcI3Fi54RfKwJeiDjPTmrgU9tKNBNRTO/8LCcInPoZpHlTYrWBt8LX4CQcsYHILzWS1SSjWYTVuWWmp3QlSQ0LyFUclMa2SDYDsjYG9G500vse51KeYznNCDaqu837x+x5XMnovWnC1sQgZUFgiFYEVLsT7s4RGVRBMZGaFLyjKMojt+qxcnYqaXrNFObkVOaLjvLQ2j88qMJEDIj9EhSrykgJc25y0zBjka9kndpEUvBFZfK9Ujdc1uw6sYw7qogQzaWb8n//KhqRmdD5iSHmWDYwzKgTkTINHVv8gkleWXp2rvJ7QHp6EXIkFolAZ2slRm8YXLbQY6lHrIg6qXJqlrJJ+wg1+BKpJ32CtBlj7TiOUKDHYEf8F1qa98MWMe99nDfFTfQPQ3BAZYirrVNvmlxC48Vy4o5b0xCg8JB0Lbxf78xSsB9t52S9nXtrbTotsbOpAWKDgFBkJWhABrj9TJxZupPCiQGPYHtSr6mdtcPEAhbW4rhrlCdahWSmNE4Wm1IMhjMdKQIESPcDNrba8urhqNS3SFWmFQEWS1frPtOHCIxyNh7tIfXLFYKOXG6PDsYnPc/LYVWrvejDJjKXz2s1en4b5UixlpW1wZD7yYXmJQY9dkQ2Qyjpab7ToAmtCi9/07d72K3SbGe97Dt7n58vXrORR12BPqP8kxMPiQxhXeNEmyAE5Du1JSAJcMw7QWt7E1tU69C0KRXNQIP3qK2fGne9i5lRA/RqHczHC/5zEkONGpbZxrtGIRorIpzMprNuZCcFHurw6L+BPueMbSslalYFvEJt9gPxToz3CoU0sl4ZPs5m+Br+ldvPJkV9+8r9yPRWsUqXDYLMYXKVUUVaWnBmXIAyoF+ihen3OlgNE23Bjkl+RwoILRM+yJtoSdTBNEM9wbjx8++MNfvrc76s5qMps7/ii6kE3XoQV/hg3rG9JDupq+0nyQRi9WdkqlQ3DUHo4hA7vsYBF3vmA15SZriyoyjSULXCeY33BwgfvpqaCoVilXtxJrffDYAajBLNM1QqqEk/gzcSYAL63K2fs3NUct+u8lLvD0DmJrSqxXZH5aj4f3Dg3vtHOxUgspK4yJC0HxfBiaxWqwZi7JjfFgS/2MNn3z5MG3X31lU4Nl0nf1TupgGCnS7xBzrXmFFoVEtx47W86hxo5FOH32xOeCOdQpGgbTMLeDVe1FEw7zbAqToQIKwazUnsdmPbxFZ1IQf4EKuNu+YZMtLtRl+5nUSiSTaUX/aFSUr6RVxrgQU6e4yumDGEsqijiz0AWpRknG+FWG8kAo1i44dFMlsik3uPnpIqDBq1RPJ2iUU9aejpUPCmpOUXpQ76iaUjV1eKzWBb4ic7v6JTfe9OGrrir4xlfyrAO9Aw0iQGO+qxvY4J6I/eHxsQVR9qPuOQd7x4CiifCNYm2py47fILbYmQrrUiuo1dPLSAUDN1dGG7zqdpVWY1DulhF6GosYH0ZaOCc529jMR9h/6xoygbhmfO3HzQxiS1NH+JIMB65xISFbk2GeGdlP0jhco1HFGxuOqFh7az2zo9FmUtvm3fV1p48cHxw6cYTknNV67/DgxclZLi2RYC3jbDOpGkWDcV3L3iJkyQy4VXou9RCCtlSr8u3jJ87ns4VACphGjj+Wfd0rKC68X/GDYG10EOuN8ER+igJ0GlOY2s/PAhs/50eSi7RpGQALoNgHK6mQisIME41vykj2Pc39TF3ghZ7kseJRjfr3qcvAGu3BxuFTJpLbDVAYQU0d9fOCWSMQ+DrHcswF5QE0yYv5MTutbKJxVUkDCG6w1K/A9FlKRjDuNyUZmKV0pfhUYe5BqDVayFLKbQTnC3Ntg6ePJUsllK2C4UW1KiNlgHAtYaFNDEzauCpOLkhJOvjmZL4GRKpm7fr48FAPwGl2h966u7Znd9nu7Y7P8Goy8hXG0Lazt2fPXj43Um+Zf0AJw7FDnZSbh4+76aEHftQR50tplupSrAkUleCvKZx+ibiiV2qZbAai3nMrKvyz05vt+THMsuwHNG4gTkY83KNzg520T3y8kblkNWfgg0El0PTjs+dew2NxqoluiyksrmLc9oB+9fjhL796pDNyfHRodll0Y7igVys6X21DkwQBhZoFVFP9EJ0FI0nvE+S0ZHPUmwNbm9FuaViECtaXTlUG5bXHt5wy//HTBUyLKfNeqRfMwVyEvLongNzDHDTiNnnHMdJDzyL4ypabddbBxwpAVmYVK+Y8r3jjr1Jqy06I2Zd/HrBtGQKdxgSsG5dHntfVXlQlGKX1tTxbaXFpcilHxp/bgLIwudoKVffd1xAIUKJK0XPU46wHQEAWQEmpPAUHtIbXS3V6LDdjALv61FEB30yzbuvgNz8XLAOiisF5IFcB1PwDLoSG+W5Lk6NWxUDMtHSTISet+Z1g1SSa8zKen5w9e32elm/Y2KhN4LU39TVx9fnrF989e3r65q1Bx9ZVZHKdi70wrKqWV2mxjerLQyEtzFFZfhsGGZQV11FrDTQNGepYQm2PaWjDqyOjJOiIm+ICm/LLTi+WFQeFHxiVyTCdrcbxkupoSR6M/XweQqF8a53rrVFID/pTzfu3b05/d/H69atf/uLr0WKkarBCUidJ+6dt0kKlarFhjDul6KonLyRAOWks4pAj6fmbzWLtEHZEsjPtt+9s75xttp0f8pqKBornEKeMYtGVlLi2LvRlQvRIkJwylhH9GNDyPGVQTVn815me2C+lnhNKir5Ic9ZdKk0F08uxhzRgLo9Vo9r5rEq/lq//xb08Hv302d38n5YHWmn7gsgymKryUKs5ijWRuJjBlFvBGUqmRhRM8bDuYUT75slwPQ41RRLIuNvz8i9fQ2kTQQsGUCnPQC2lPwVjK9B+TPOePdAZ1cioFvCIJo71xPCGtIlDt26MCT18+Oj7l6+evn51fnnx3bNnwpZproza6S2065+jpJ+KRHMw0hXqDVaaAfeUzQtzCWEoGA0pU7BmPgZ2rU7vXQVmAAz00/4cOcypekBSZs5XXMSiCn+NuGLUhNP10ox8sqIdJ3pYbArBXFAN3DBTcRLw+reTp89fiOxazJRA2jyEveHFdDbWf3h9/vbj761eRQiqri59Owi12ihAbFdfICNz+FnZLk63BqoO/2Jf5RjpSyiU0sp1or2N13bqNCjEfDo+TMCXLmUEKkrOac0UHnZOWhmW3mCGM141zqgbEYu/L3N8rdbYkm3Ay89R/+6xAyMXr1oVrQSXUX2TWZYKV/X/8ir7T6kpXzV8ztzvqpU4dSYv+QM1aMmaBP2eUn2tikrCgSlWCpDRFxdLi+2ZroQ+PoNfUmLukOnnQsXoSZBzhLFiaqQbuaGAVILaldy9qtP+MHPRg7andsaPh7Jwz9mG3KmtSdbNRw8ffvg3//bj9cXZGxoQ0wZgQzV0BlB77pdKU/80e5FIwCnnNNiqUQx2qfVQRoTTOmBEtSvactS3by6EVEO4iux4ZqGN449FqWptK8PbumqMFxmppGrmcnSKUy/rOd1lmFpWwUXMrEGoo3j+9s3f/f4PtjjZ28S9Q8bEmQg/BiS1uErap2/eeXFc+jHxfYSlcHKUBU79DhNMZDuGXxKaz7YuxMSGBXOykS97PDQ7Ymaw7nQjqo7Cva1qFJAR1jd7InfiGQDdE8BSS2aBTFDH5FRazZAbQaTEoVJBoVQedLzUKo2LEzL4BFxli+aCXSyJU2VG1mgS6woByfPZB8g//ej+px8/PSt1csWhapFl2DhZp8Cq1DxfAMZu7PXxn1z9QqRsmq95CnDQFn1OrWsLivHKmga32V+dUuKGsvIghSdfsKmaRWT5/MXXVeOM2w9sXBsNwumpbGHFUJF/saUqpHI5kKqT8/DBfaMsjp1WyYo/ScwCtuvLT04W0z9uaVqYtINU80wD66SKR5qfrQPAgdavc8gLxe7pSLoYa2Knxj8JpVdKe3uh1qBTaGVSD8ihPdogZcvLDG29sS1DcJF4TCM40qtorNkNob8daoNoSsCa9Bl03FjTv/m7v7Ncg0oIjIwEAz0NQnVg7PB8CceLjgGej3EOExFhocQwh07ZkRRVLkwpcHKIC0/fuR0anQ/2nG583NAA4LcpSd4fE/HVZR3Lq08nYzw67m1EBKEKM4jssX9+DHk+ibnmYkFjDAILp8AMoS4oZXNLc9RvleYKlUrG/VYLUtVermp08RqJudZw5SknOTzcBGaKypAbzoIKbnwCX04fc5s6fsbZt7SeLuVVsKCATVMiZIANeAmrgiszmPpgswBMp1OCsXAYxvdhi4IkO101JfSlUr5G0sNNOONLZmlTy6T+1P6BiJzF8CZqCNE0m+audtFXqdRBUt3Zk6o3Gwu5d3Dw9sVL26WYXw/GM1GYUX8Go0KOsLJDHSUsNOJyPOF3pYOXWObiDafxGO0fk7lMdxzGk8J7KBex8uSVMoWFoCqt+JZhLH2X3U8m8grAFrh6s27kEbHZcOORmSijQvnBXPv1H7//4dXpBdDOKLZyqTXW0QHiSIMzgXx5sZivjFMLrhCodo88iL9oTstwU43ve4d2Y/8S9a1tkGONF5YXOX/y0+4V8tsEan5B0+roWYMMXgbhJAqUJ2Ttg/ZqVGfRHjXVkKWA6sVBaI7SqgEm3TfXGybwgxUS4nh30kfZug872uE2SiIr6lJn+I+mDoGjsdWsyGIbZa72ueAYF6b8JEjP/7qA63uFQzfDaTVyNUuxnOMybJBkBm6OY5Q8fcgIYivB5tH76tfI0S1aPF7gVTyhxJD+lmseetKFXk8CUq9XlpDwWdAQi6ZBCS8AB3OgQPzMyWZfq646qSxijI1+eP/Ows1GX3q7H/gbRhefPHrw3bPnjUYABbJJ2Wqqe5arkMbTLEwDLPOa46SCHTXUOq0djivGcupjOJm4JW3tOzXaMrvYYMQi6ItOQWUjjVQDmRFCf+vVySk8JPC/WhSsTRnnJcciO7eW6bVutlLrXoRrdOj7Z09/fPkcCujtLMOEHvikCvfRr9FA7JNSvVU46bIOXYOCQh1mQRE9TxzLl2Lw6EUNrPnq6tXWlm095ud7z2iLpBytp1lkxbwaFl87Pdzufq+vZRD4kvXP3MLAXJAbq0O6AlMzNJa7lWUsIk3CPUdE0ls5/XCHEcJGVhV1wVVm9KUbQ+VU59ZVeqkR7/98BrA0QhgNrgnFlGpairiJ/kGwFMVqTSs+WaBDZFJmeKAf3payFJ48Famq/38aA54TyDaEuvhGtUlZVcuFKWPxFU00MEyYaeDooBLqGsCf+SdlGDQA3IG2OPoSYhMRQDIjnAdEz7cSm+0H0vPKIuEOUtn4m2+//tf//j8qPRoE96X2z4YLdCGe6lYmODoGyaEzac2qhfCdlCjoGhvP2dF9qPhfMONGAyczAcB0uEZhWlHHEjQ33ukklLq6bha3wOPTRzG6d6t9cMbihw9zfoGjThshPe1VFu/evL3QfSGHN5cfLeILYnKBFZQhFH7zf6jzIxHHFQThLy7EMVf5XIav09RRyppItFuW1IP575j9l6cn953NlAPUSEx4N7RDw2yMWe29nd1extOgmZ7Ppw6+UWmqOyz6zN9qG8iD53gECSEWUiv2LKo4apsSxCUuSurQ0a/JEYkL/gvpfhTqRG0ZKrZkGV6slKenA1Btw48hIziBnUdLwRAdXjLB7itftWiaTqdfk7LknioCEbXydS2fg2Qspfyl8hU997cqXspwYEnxMDWKVNxbGpKF4ikWhv7HKuXlSEFrNrKsUoo48qr4SYLFVQRG+HyTxWnCEsK2W9SYPk+ut2BRqrWeZ5fvQZwa0okQrJqsBcnhVM8z/oxBxJgYUK35hx5MrBs35i9tE1xsNZAKmjU4d+7c/uKLh3D4j7/5fVWMP0IqhayEaYedXQGHE9fEdDqisWHpWLBojQMf+/Tls5enL53VHHESO7NI4WaRvYNxsIRpSA0lPYotfcXs+aym4RoeVXpEEQJlHKJwlWcJSKlD+oo3axoiB3Trr3ihUCwueORXiDAlaSX2+oY1SGsvQDOPyGjj3WdOuUlQSz0R7X5SauTS/5xlyI5jXGyHKCswVETUMGuATuLgLXmFKXgDFJTQ7391LAAmbzn9X4r4gpKay1bGkvu/ZOpxGHUFt2rLNqX/gZalXKnLv6XuAVSxyT4w+ghe1YAsekRqZr+qcRHLUuPUM2FDcwlK+KuvNGjmFFxppMIFV4N1FA9rcNLKeq5pGoOGPot5xyqcfCWCzSPXDF6ZLOag1c9qdG2dyXfq2I6lZarMT/hP+aG9SqN0mDQURU3eyiedHfwnE/siMMkLL2yOe3R8+KtffPPLn/3s3sHhd89ffP/jMy8NHAtoBcfg3q8to5ENKHlV4yz5AHLqB2zdnJxf7xzy/M7RubEOkmRoskIrMzttxoGEZTXH8i4/h5ElLSmlTpKEqp7kvqNt3EvqhqcxdwQfhShrRkFTIMTTP2h8AC8Heya6ZDSiynU49Uj74Nwek3DyE0mAVo1HtUxNHMjSJ05dw2S+p1IBVfoxFyKnxPwgfFY62A+dQZq/Je+KwEomqKpZRLDkK1MQhualujgp+/i4KfI555RO3aaeFfjP8AEApqxhOfD6WuD7nAoWLD+X/IfvqJ0LvavGIXBECWBm3nKOaa/l+xx1F7tTNduGaiNGOqpdWm/AwBygoZK11Fqrv6mEOqSS85tSxM8iic27+0YzhRvIszVQHkxuiOXTewcfjzmCEsQYgIs+lzZ7xuYWnnhc01ar45rM8z2NWJ7R2Ikj7+9b1HB3n4EZVLRO5+ju7aOjfVGWBuGrxw9+/Ytf/A//9t+KHUDIhBaXaufxu0uvvWl0MA9b/cnNN6wEe3ivwv4KmhvjVxjTNAjmh8teZswMrT7n/jPnF1xTt+DG8yFiIRm9/SpvpPdDBjdpkhSx2t29nS8fPfRGLai1/gJz6zCNEuW6GmytQmt621u9ffLiVCdsa7sGkRgSR1VophcEFi4rF0bDc/EWaeVGUgU0D+HKlGFMQDQHm5ZWeFR6D7uWm1HywX+hYsrHtKqIPQNIXWkL7zUlFycLu8nn4VI29KaPPPB9DNzhcY8kCNImxwoRX2UZTOb5QJ/Ez/gtoCo7KcuNe5j9ZJ86mqtTMSUvsY7MNb2yUzwVTABECxEgyyCjOJc+XsPdovs4OZsfFWsbis3vW1vfP3818bqjfZpUtTCHO8MLRpALvrpuVU4xSrUtjJtvTKquSU4YEkkkvP0IjUQPNV9szO+tjVuWpv3tL3/27eOHd27tPHryBDH3jo7kBz9BtH7p1j/521/9u7/7zfISE74VATPkOst/GFNcGXeJKKUgGhvidBioemqdFB1lU8icbjYw2PmQM3kMj6axSuz/oDnXDjFHftqcZkzvpC4/1jpiVZ+5TZWmy4ypWY9+946drtv2Njhs5sHRAyfEfPfjjzUJLbuuVTBLbm45EY2mG1bWEjAGSz3YvfUcGx2D7kgy+7C95MEwbG1EurxSm4wtSiPUP7jHKTnSqigfzkdRFfjhdswUytPyypfVJIAxaM+RolI/u9yl6NW4fPSDTTEoNUkKANjplLskXM6geuj/6qcvOZdMITs6sIJdrvJP9qltVWxS5+nnj8+5omfCIxCDnHIshagy/MFXHb3C2gWLEKwGf+rHDF6mJbd+ozEDqA65pgtXhrSC0tc4a6atgd6+5UwggtN3tcCHXMRoRnUM8tBmDYeBGqP+4E20OzIZCmqL0BvscK2dDuusq8HCjEdpRESHrJy5sTUzwQ4WEkgrqHYlrDsKwQKHRh6//erLo4MDr71kq4TZHk7fZqkMRKkDD8CMOANeKTEhh0UqIh3DQfpkRYcQwjxaEV/M8X+Q7Gv5OSiP5sS3ZDac8jmop0gsgGk6VZLWtt7C3IXCGzdeIPDzJ0+eeNGI1XY7t4w1t3bKyS3rN3rtBnPVOYZAte3bALkQX/1Rc2vTWLC+pCOmOx9yyw7BHX0m7oLoBXhn3op1ce6JWQhURs9Sq8dpZKqY1g8Zo5B+sIywl47tky2PvGSKU/ZGhcBwRw5JaVejcgtWQolgVNE0eWGKr3FaDmhM6aqQI7EEAYiSAx/7RsjBmLzzk3B4wRBpRLtVn56LFvUOg17mDDtkhk3Vv9haCbAdk6pIwpVWgerVeBYr8JQJHj4yWu7WoGeEBUaOQVShYURNxljRoJfEUxxy8ypnlzJ39u48ffGUgKw3a9XC2ra2gEDBrlOhF+3FKy2isXbZQI5ot7Ec9SNkhFNFU2cDo2CvmNjoVENhg/uiXrrg9dHNUO9sG6T6xKFWFjaOxoq6Io2jzc1f/fznPzx/rg5ulR9GCrSXWtWLecMt1DbolkQSUDrj3nBqO3X8KWlSuSchUbYMJl9Q5mHPsLbHflYYcDstLZKIt+mVU/jskX6fxZkIjLVq3LSJaW9n20iCOMcnSbQy/Hptd3vHQfZe84hOTGe2evc13vBM9FUNxE7n/nqP07vD/f1ODTAOZuF7K8C21z7cvNncUCn3s7dndo49+CMGZydueM38AG7DRfFgR2tF4Mg6ZVjoklbqGNBCYVVHXkzIZ0GNWCbKLAMUY8nKFBQsR6E5SHr8SmHOwrEV2IWhn1kZX8EGoiqmdjd+RBspqYAyBafXd5B1uxUqUab59KHKQCSGuB3KLnjKE0VdPQfWXcBK1T5QnUr48HMrS+mZYlMioP4ljUr65849FsrieLg9rJ7lFZ8088YhL9+/t/1GhpEsb6uVvvKO+qcvX7559+HgcF/TEZb5kXZt5SIpDpR1VgvoMwsevAqyPI/shzaOn0qQWk5Hwc436dBiEwlwBbMFFyTS4jE+0b3R0e0vvnhiNfaEfHFksW2tEuFh4TLPklFjgrrjX0bhxjpYoJqN12/VQ9DRiQ2rK+xXvyatj/kPoZjkYicjCrBKK3KvFZroLgs3faylUiirwn1aNYKCmIq1sgZJX2yc2gB0+8ZLzejtAoekZKZGDa9isWXbFxcXXpYU20QBs8E/rb/ZJhV0+mNmpiZ0rSyENFDsxbv3Ts4x3Iuyncz39MVrPTwDULnXOUzAI7OZMC8QaJakI6ORvxj50FjYn+Ao0PQ7ojDhxUCCgh42pGuLw14ccDPMcYcoAG9HH/WITyxxJhJM7KhjUtKxVK1gjH3pbNKDKZ/eDDZC/Tz9NEfDu9yaJz13hWcYL/CqN7OcWeT5AT/IJoHhbPSNxKEisQNUBLOjMeErRW29iStGj/aP8+C5eH2ZnaIoggmxjd5NIzx99uoEZY4/UUut7dn6j89f/PDixeuLC2dRHB0dWjNm7o27pNuExUlVBwZaiz78Q79GQOWUceHtjeUVmNIryil5a5khc/L61cerr9Urz7CqUjSKgo38oovPpRWWCQVnJFuzMfdDnbQZWvaDgg0zYg/+zuKL3lQ3hyozx5ihrqk78VXHqkVGaQ13XPWRC+luRNHn3GMRnefHY7SLgWox7dwDdzEJyOPobmIAb0PAIzJsFeHuLp6PH2jHVjaTvFvyYLH78dG9f//spQDJKX0OFQC5GltlpWne9puconIYWZSob9KbTfbo8I7WeXP9bPvNq9fnUGMIYjTtgcaa5QrkICIs5HLMV2hUoD5cQ2BaEJmoFY+FcK3cEkLX0LZFfDCZEsrFrBiURyfsQQeIuDqmFWhy62tMfUlPIYaBPmyDnhrbQRoCHFms9b/af7rtZhIrlw2FZOaSUPwf1As4xqGUY1qn7CARUhoFBqj8CQtRApgFDZNVUFbfUljIrEEGiq/JbmlYu3LbqGk93b//7Z+/f/4aV4VALU4by4FBBnN17cxqxzogcKaMZiog/KAVvtAYMiJiXJRKekRr6jheW39WgqlrMvRupPa3fHgHjfdv39J4izIaBZ14DxGfLt9tt7rotg4qNGgxXEQ6M5ZUmwAatGvLq3xhIM5n/TWWDMtgUVqPfyGUc6UVk9dHRaT3OXwaFS3Br9AcXOcZjPweqeZ29Esyfl5YFnQuearXlQF7tOVAPop+0WmqlNJ6QeOkH0yFyJXHJaVZieAlwXZHvD49t3d0c88qPYu7uZCOpPWyx/PzN45i/XR/Gt5F9mOJjARh4KB0/44jzF5KrqXSEd/2srNrVeO4plZQ/ups7Td/+KtBuju7+43XzntZIIp+XpluA1KQUNciiyPPEhbHkQL2KyPxCLsJomakPKlUbBK8Zro6gIrhVIVBISLFK1SueeTBqt3IAw5U9I4Sj//LpUpP4fl/UDzMCtKrRDA5Yx18MrMqiJDcfj9CMP0fNCq8wAv5ZCqflki6GOH0AnfPHIL9uEV1gojGFcvReZUbD+4fn/+b33jbJuBAMwZHHJFoFqgpnL4I57K4uOkEc+4qwxyXc7kJvP6eLfK0PL2ggbRi+5Z5JD0NIyj8poEpbDy59vrGM28RYGPCh9sbzme52l6zJQavrm2DhMHu9qYto9cWJ1iNsX3rYG/XdpoWKAxjxsUMIzRDKXX23k3f6xsdODeMwAXeVnShbRyeJtuoxrexBzcxsmsSAUnAEW1UhzkB6KoWUihKInSbgW4ceu4EsYdetDqvtMFNU3u14Wa/t+z723WqKpo1vRwTsxcNJVEIAaZDsLF+b/8A/T+8eIW99iihklbZ9uHgSy+iNDl4tXe3brpVevMyASs3cFW/wfZZJ6Fby+edvvp5JHDbWOz6hiGs99fviJZj0rpaH+t0bgcXMK07u3cjoN6/txXayLrNQanX4hOC8l6jH188lUGTMtJs8jt/pvPTGkkWn5iXRYTYhAY+zqFVsS2PyjiycLSjsHKaKV8LnytABWMd9SycTdfjqmzxvhO2sxaJPWUARmyWbgtLJYq41o6WKZScFFpJu5gEXaIvOIw6j0ZKlsGJ9eWTn+NuVc6Vt4b+5YenmvBdvdTbu3gM6gx2j8FNFU8ePtAZ1jNYFGKEUmGnvuom0wedZgVhOMTiTvvuUazxJ+hPbxwhVNcwDszI0fCycIb2O0OCVkB42MsIr5+9fHX/6Mioi8oJwzoPRzaSOjpqpm4272zf/s9//jXb+OLJ473tnUcPjhn1BHPDg7iS2ScVOh9z8me9lay1RTmGUe05whZKOjqJby43nmZMsT42+/Y5XmHYPB+7uwYTxBf1JMECEjsq0q0y66de13P8gf61vGiz99sacPCQ0mhkYcMgP3y8vXPV+AMQBYI1L8GgLHd0uHd3/vrsxbmTyOJ6SPAlPONoc6+O1c+hXkrQWH1zMqOuPKJGRRDrQNh7GpYPHa+g3eN18FJZtFEmxSSIwU7Oz7A4K2rxlQ3cOT/eheXudALszfn65veOVrt8C3OIpD+rUQ+41CkyTmDNI/1gugoyj+KKXszRafWaQUZiEIX6Kek231VIhmRxc+C4RnQU4vGr7S5JQ5kd8ChfbIYYdKQlsccRkAQCSl0gbGpG8RivJEbCYEZpgPM09rmZA/ZqtqpzOC2xtc26A0UXzh/1boA7e9uIhGejii23KyvEUr7r6/uHB0d37z47Pa1nQS2KdpK5+QQbcnA1Sx9r9w1BK/2975pw00QdXxaQF8gwqAQdgBi8Z4SwI/LVCxuxc7VeX784OXnz5uJg9w5pvd96y88aK6FgsQry2Lu59eTePY3Eg7s7jZ3EAx7qM4GhOOQzg0qMfiLMC3QYLDpl99xgizbFZmgKJWO8ASG6Yt3qJnNAc6DHhAJIb8jWiR2X786GQeP5liA1AKKLtRMjnW8vdWhbgC1o4dtuo1/lG8aJEaxWptDY9Kw+0lFKhxO1N8V7Jcz28b2jP37/zFK9CFANsefQreX7RP8+bZga7zwlRrq04CyKqOSSmSyom/NjPpx49Xei8XFn6oU5qffPyg5CffVSlyP9RaDRiWZLuJxe6YtuiuBNGSxVeSgMX7K9wkAtIuXW51u4g2UxbhkC0grAN14EJ6JrB9zM1dMJNyoDuWku1C+vM3VEwtijies1UMxICM3Veu3L148fO4yQzclAPFowXUjMUfz88vL7Zz9ShfsHhz53BA2tD92d0TydjbHC9Zvz8zPqTnDolY27Bhl/Bo3Nfe9h3+WtUjHYdJbhRDlkl8WOWvAvjx89+N5BvMXAWJGGQxUlyEWLW80LPzeJw4NxDY3yZzDXerc9ityuMe4WVzsSBgPiWXxOZWW5fHNpBuPDwXvp25+8e7BOczaWr/C898AjZ80L3gu6FG+UsgG4BTwxywRD2Um8ZNbpPVJ4SgLlU8bZwL3T5eP7sb8MoeqrIBxkWWVbEB7rHy5Ri4017+He3hFLyI0fCIPq4h+C4ZexNov8jg/32dvaHbtaIxJQCuJV8rBnKO9Fah93PlkoOCugPFpcPKXh1Y8O98EpBJhaFB9KUiGW126NXmeP/JoK2sCeWVXNAbcwqr+3c+fl+kmV1ut1mBL14H7s/QO1LqSXDGlivU+RA/emipiTbHVI1oDmLJ+fnPz16QshLRQ8g8BwZYSw8IcFufEBzW4ncAnHcS0jnMgWGvmrXJySbQqVyU+Eiw+yFe5ya4Nr/Wi9wFTaUkoSc37P9Q3XQGSz/j9e6hLy1EI/inV6eX769hw0U1F+apA0VeCaixGa1/BE1LU96Cyf/Y/lrz88vg/9vbt79qFD0kb5+0f3Ts9Pckh1sovoOBEARxB5D2ODXz959P/9D3/PXkZhItM1+ce/dJ8bjc4Qx/jG/9lU2WLVEKy+CtYwZnAxxeveHKG0JZp9cv/oyZPHr169fvHiGRURRwuvCiFu9RJy9jtiqIjWVd/PjmPm554K3NnZm1WbC3gZdV+Td+ISxF5aaupA1aSZlKTWrBt+Ki4ioQQkc7nTalXUGoZ0yWwdQxpvWemlzoZVdLsN0niM5sqOiQVKKR7l49XFxRseaLvjNtKQDKUaUlM6enp6PlMxn3avN22H7kTBqu+0i/GfW2ap+T/RXPgo2dgAvlK1gmbtbKpfo3Kl44bYYh6NjkMAE0TIt4SpgLJeJF+STjgq0FBUTtqO7nW9NGHV6dlrBmetAFYaHNJyEr3TKU/eXLw+O+NByBBTaBIE40lkhKtrUvweFpZrScGQck3qpEx4OWXJo0zNLGFuSfjXFigtGwYbL0EjXcw86gFrEET6WsYPHd5s/GBdnFm7x8pwMq3tV3pvObHXFHjzUQTqZjAJljS8invrvS6DKD3lamaMtIMGyZT7UDUBHh0dvH3/JkZnrGKjOjdUZ31HUt1Cuwa+eHRkdueDgf8hP37EiBiilohyh4Z+LJoUjZ4NS+aOlOqPce4cE1ve8vpxmNzZ3v72qy9+/XNvBXyg0fr7P/zp//7/esrl2bZPKYyU6o1g0ua1HrkVpThEU3Jn79+/hXyz3eZ2OxIDz/zPD6UxvkOxV9te83DKhUp4o2FT9YXawuEhxaPwnvyVwQz55n/+YcYNsCV6ysqOe0YOs5R7yJwWq4eWkW5tOYgDLxxyfHd7x+iQsaTF5OilUlwXIqDYKNlHq68/RKRTakR66UAMun/YbMHLk4uEiLc42yGnZmRCgRl4J3Zjtlpb/WQza5mlAWyjQ7JymSb4dkUAMqzdnnO/x5AAVwM4Ygw7P7yV9Lsfnmm+zGQnmc0WzApL7N1jZSqqMk514UafI+2YtrAr7Z/LV/VKDsGU3DVq4TuEJpfyWZQs6cwYrR8lwmqhMuYnrLyoQmIXPLFW0mEL+OlUaFsPZ4SgUZ1C/LWbt+/fXby5tAIe2iqlLnY9Ye+gO+BRMW92Y+11oBvcy0PRad0E7oALElnc2zw4PT+toFBna4O1sDoiMuQDAHAMc39nt67CyVldhQH7mUzUNL2kIp4gToyVT54mAfw2E0pfhz7A39+9s/3NF199+8VXB0d3LLajk82lmpy+taOiJw8fOYjbvC1OpL3DJcg4o9Rt4xCxmENfFmLkODhETdC8KET2sYW8sOzUZ83bCVpxnZzqsIYde3Ij4J7kHvnfZ+M/JJ1PcKm+ZmTkMwmBKS2T7iCn+ibWn5SYbrlxhP6Dwz3ng2Pm+dkbLRq2Eo8YiT1EoQcN/nfgJEBi9I8fdIMEgnuqADuUG+rOYVuE+OLkAvBQo/0tmpepvdt8ILoYQP875+PD3p36HpHcfE0+l67rKF9evqlBcuAZ1equ5q5WYf3GqpYHD+9/+vvfvvt0ffHxYpigz1dggG9RNaSl+8OWMHQ7l/uyJHHXoL5wZ7gZbYtJzNMogHdFEuHSSwja8DfuT+dThWUJJOn1XwtGh5hBYtZpuXy3c2vjttdlbTWg7J2GmoEXr17/+ekPb9++EziJc9KF6kJqITv/H16JsfGopro8cXjWrU76kS6Kvu04rk9Ki6a2nPn59uKdTgCMeYM7a7v4C6SfE8sAfqU7cfM6pMP0MwdiGZ815hFravwMDxjlvH1wd9ff/Xv3dBG98/LN5dsfnr78/ulTY4tfPDz++tGT27vrlthgGpMLfc3d5ubxvcOff/PVH//wx3EIosukW/iJR6lpHl9OfSp/LnUSKjX7nwEuLdxbX9webwAAAABJRU5ErkJggg==",
+            "text/plain": [
+              "<PIL.Image.Image image mode=RGB size=259x388>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "example = dataset['train'][0]\n",
+        "image = example['image']\n",
+        "# let's make the image a bit smaller when visualizing\n",
+        "width, height = image.size\n",
+        "display(image.resize((int(width*0.3), int(height*0.3))))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "826SLZx-ziCs",
+        "outputId": "dc7af551-fcb0-48bb-857a-2ebec1bface0"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{\"gt_parse\": {\"menu\": [{\"nm\": \"Nasi Campur Bali\", \"cnt\": \"1 x\", \"price\": \"75,000\"}, {\"nm\": \"Bbk Bengil Nasi\", \"cnt\": \"1 x\", \"price\": \"125,000\"}, {\"nm\": \"MilkShake Starwb\", \"cnt\": \"1 x\", \"price\": \"37,000\"}, {\"nm\": \"Ice Lemon Tea\", \"cnt\": \"1 x\", \"price\": \"24,000\"}, {\"nm\": \"Nasi Ayam Dewata\", \"cnt\": \"1 x\", \"price\": \"70,000\"}, {\"nm\": \"Free Ice Tea\", \"cnt\": \"3 x\", \"price\": \"0\"}, {\"nm\": \"Organic Green Sa\", \"cnt\": \"1 x\", \"price\": \"65,000\"}, {\"nm\": \"Ice Tea\", \"cnt\": \"1 x\", \"price\": \"18,000\"}, {\"nm\": \"Ice Orange\", \"cnt\": \"1 x\", \"price\": \"29,000\"}, {\"nm\": \"Ayam Suir Bali\", \"cnt\": \"1 x\", \"price\": \"85,000\"}, {\"nm\": \"Tahu Goreng\", \"cnt\": \"2 x\", \"price\": \"36,000\"}, {\"nm\": \"Tempe Goreng\", \"cnt\": \"2 x\", \"price\": \"36,000\"}, {\"nm\": \"Tahu Telor Asin\", \"cnt\": \"1 x\", \"price\": \"40,000.\"}, {\"nm\": \"Nasi Goreng Samb\", \"cnt\": \"1 x\", \"price\": \"70,000\"}, {\"nm\": \"Bbk Panggang Sam\", \"cnt\": \"3 x\", \"price\": \"366,000\"}, {\"nm\": \"Ayam Sambal Hija\", \"cnt\": \"1 x\", \"price\": \"92,000\"}, {\"nm\": \"Hot Tea\", \"cnt\": \"2 x\", \"price\": \"44,000\"}, {\"nm\": \"Ice Kopi\", \"cnt\": \"1 x\", \"price\": \"32,000\"}, {\"nm\": \"Tahu Telor Asin\", \"cnt\": \"1 x\", \"price\": \"40,000\"}, {\"nm\": \"Free Ice Tea\", \"cnt\": \"1 x\", \"price\": \"0\"}, {\"nm\": \"Bebek Street\", \"cnt\": \"1 x\", \"price\": \"44,000\"}, {\"nm\": \"Ice Tea Tawar\", \"cnt\": \"1 x\", \"price\": \"18,000\"}], \"sub_total\": {\"subtotal_price\": \"1,346,000\", \"service_price\": \"100,950\", \"tax_price\": \"144,695\", \"etc\": \"-45\"}, \"total\": {\"total_price\": \"1,591,600\"}}, \"meta\": {\"version\": \"2.0.0\", \"split\": \"train\", \"image_id\": 0, \"image_size\": {\"width\": 864, \"height\": 1296}}, \"valid_line\": [{\"words\": [{\"quad\": {\"x2\": 244, \"y3\": 390, \"x3\": 244, \"y4\": 390, \"x1\": 232, \"y1\": 372, \"x4\": 232, \"y2\": 372}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"1\"}, {\"quad\": {\"x2\": 270, \"y3\": 390, \"x3\": 270, \"y4\": 390, \"x1\": 256, \"y1\": 374, \"x4\": 256, \"y2\": 374}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 3, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 354, \"y3\": 390, \"x3\": 354, \"y4\": 390, \"x1\": 302, \"y1\": 368, \"x4\": 302, \"y2\": 368}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"Nasi\"}, {\"quad\": {\"x2\": 440, \"y3\": 391, \"x3\": 439, \"y4\": 388, \"x1\": 364, \"y1\": 365, \"x4\": 363, \"y2\": 368}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"Campur\"}, {\"quad\": {\"x2\": 497, \"y3\": 385, \"x3\": 499, \"y4\": 388, \"x1\": 446, \"y1\": 365, \"x4\": 448, \"y2\": 362}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"Bali\"}], \"category\": \"menu.nm\", \"group_id\": 3, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 388, \"x3\": 618, \"y4\": 388, \"x1\": 542, \"y1\": 362, \"x4\": 542, \"y2\": 362}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"75,000\"}], \"category\": \"menu.price\", \"group_id\": 3, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 246, \"y3\": 418, \"x3\": 246, \"y4\": 418, \"x1\": 234, \"y1\": 400, \"x4\": 234, \"y2\": 400}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"1\"}, {\"quad\": {\"x2\": 270, \"y3\": 418, \"x3\": 270, \"y4\": 418, \"x1\": 258, \"y1\": 402, \"x4\": 258, \"y2\": 402}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 4, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 344, \"y3\": 418, \"x3\": 344, \"y4\": 418, \"x1\": 304, \"y1\": 394, \"x4\": 304, \"y2\": 394}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"Bbk\"}, {\"quad\": {\"x2\": 430, \"y3\": 418, \"x3\": 430, \"y4\": 418, \"x1\": 352, \"y1\": 394, \"x4\": 352, \"y2\": 394}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"Bengil\"}, {\"quad\": {\"x2\": 488, \"y3\": 414, \"x3\": 488, \"y4\": 414, \"x1\": 436, \"y1\": 392, \"x4\": 436, \"y2\": 392}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"Nasi\"}], \"category\": \"menu.nm\", \"group_id\": 4, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 414, \"x3\": 618, \"y4\": 414, \"x1\": 534, \"y1\": 388, \"x4\": 534, \"y2\": 388}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"125,000\"}], \"category\": \"menu.price\", \"group_id\": 4, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 246, \"y3\": 444, \"x3\": 246, \"y4\": 444, \"x1\": 234, \"y1\": 426, \"x4\": 234, \"y2\": 426}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"1\"}, {\"quad\": {\"x2\": 272, \"y3\": 444, \"x3\": 272, \"y4\": 444, \"x1\": 258, \"y1\": 428, \"x4\": 258, \"y2\": 428}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 5, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 417, \"y3\": 444, \"x3\": 417, \"y4\": 444, \"x1\": 303, \"y1\": 420, \"x4\": 303, \"y2\": 420}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"MilkShake\"}, {\"quad\": {\"x2\": 500, \"y3\": 440, \"x3\": 500, \"y4\": 440, \"x1\": 424, \"y1\": 418, \"x4\": 424, \"y2\": 418}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"Starwb\"}], \"category\": \"menu.nm\", \"group_id\": 5, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 440, \"x3\": 620, \"y4\": 440, \"x1\": 544, \"y1\": 414, \"x4\": 544, \"y2\": 414}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"37,000\"}], \"category\": \"menu.price\", \"group_id\": 5, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 248, \"y3\": 470, \"x3\": 248, \"y4\": 470, \"x1\": 236, \"y1\": 452, \"x4\": 236, \"y2\": 452}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"1\"}, {\"quad\": {\"x2\": 274, \"y3\": 470, \"x3\": 274, \"y4\": 470, \"x1\": 260, \"y1\": 456, \"x4\": 260, \"y2\": 456}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 6, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 348, \"y3\": 470, \"x3\": 348, \"y4\": 470, \"x1\": 306, \"y1\": 448, \"x4\": 306, \"y2\": 448}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 418, \"y3\": 468, \"x3\": 418, \"y4\": 468, \"x1\": 354, \"y1\": 446, \"x4\": 354, \"y2\": 446}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"Lemon\"}, {\"quad\": {\"x2\": 466, \"y3\": 466, \"x3\": 466, \"y4\": 466, \"x1\": 426, \"y1\": 446, \"x4\": 426, \"y2\": 446}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 6, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 466, \"x3\": 618, \"y4\": 466, \"x1\": 544, \"y1\": 440, \"x4\": 544, \"y2\": 440}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"24,000\"}], \"category\": \"menu.price\", \"group_id\": 6, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 496, \"x3\": 250, \"y4\": 496, \"x1\": 238, \"y1\": 480, \"x4\": 238, \"y2\": 480}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"1\"}, {\"quad\": {\"x2\": 274, \"y3\": 496, \"x3\": 274, \"y4\": 496, \"x1\": 258, \"y1\": 480, \"x4\": 258, \"y2\": 480}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 7, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 358, \"y3\": 496, \"x3\": 358, \"y4\": 496, \"x1\": 306, \"y1\": 474, \"x4\": 306, \"y2\": 474}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"Nasi\"}, {\"quad\": {\"x2\": 420, \"y3\": 496, \"x3\": 420, \"y4\": 496, \"x1\": 366, \"y1\": 474, \"x4\": 366, \"y2\": 474}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"Ayam\"}, {\"quad\": {\"x2\": 499, \"y3\": 491, \"x3\": 500, \"y4\": 494, \"x1\": 425, \"y1\": 471, \"x4\": 426, \"y2\": 469}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"Dewata\"}], \"category\": \"menu.nm\", \"group_id\": 7, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 492, \"x3\": 618, \"y4\": 492, \"x1\": 544, \"y1\": 466, \"x4\": 544, \"y2\": 466}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"70,000\"}], \"category\": \"menu.price\", \"group_id\": 7, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 252, \"y3\": 522, \"x3\": 252, \"y4\": 522, \"x1\": 240, \"y1\": 504, \"x4\": 240, \"y2\": 504}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"3\"}, {\"quad\": {\"x2\": 276, \"y3\": 522, \"x3\": 276, \"y4\": 522, \"x1\": 260, \"y1\": 506, \"x4\": 260, \"y2\": 506}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 8, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 360, \"y3\": 522, \"x3\": 360, \"y4\": 522, \"x1\": 306, \"y1\": 500, \"x4\": 306, \"y2\": 500}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"Free\"}, {\"quad\": {\"x2\": 408, \"y3\": 522, \"x3\": 408, \"y4\": 522, \"x1\": 368, \"y1\": 500, \"x4\": 368, \"y2\": 500}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 454, \"y3\": 520, \"x3\": 454, \"y4\": 520, \"x1\": 416, \"y1\": 498, \"x4\": 416, \"y2\": 498}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 8, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 514, \"x3\": 618, \"y4\": 514, \"x1\": 604, \"y1\": 494, \"x4\": 604, \"y2\": 494}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"0\"}], \"category\": \"menu.price\", \"group_id\": 8, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 546, \"x3\": 254, \"y4\": 546, \"x1\": 242, \"y1\": 530, \"x4\": 242, \"y2\": 530}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"1\"}, {\"quad\": {\"x2\": 278, \"y3\": 548, \"x3\": 278, \"y4\": 548, \"x1\": 262, \"y1\": 532, \"x4\": 262, \"y2\": 532}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 9, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 396, \"y3\": 548, \"x3\": 396, \"y4\": 548, \"x1\": 308, \"y1\": 526, \"x4\": 308, \"y2\": 526}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"Organic\"}, {\"quad\": {\"x2\": 466, \"y3\": 544, \"x3\": 466, \"y4\": 544, \"x1\": 404, \"y1\": 524, \"x4\": 404, \"y2\": 524}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"Green\"}, {\"quad\": {\"x2\": 502, \"y3\": 544, \"x3\": 502, \"y4\": 544, \"x1\": 474, \"y1\": 522, \"x4\": 474, \"y2\": 522}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"Sa\"}], \"category\": \"menu.nm\", \"group_id\": 9, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 542, \"x3\": 620, \"y4\": 542, \"x1\": 544, \"y1\": 518, \"x4\": 544, \"y2\": 518}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"65,000\"}], \"category\": \"menu.price\", \"group_id\": 9, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 572, \"x3\": 254, \"y4\": 572, \"x1\": 242, \"y1\": 556, \"x4\": 242, \"y2\": 556}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"1\"}, {\"quad\": {\"x2\": 280, \"y3\": 572, \"x3\": 280, \"y4\": 572, \"x1\": 266, \"y1\": 558, \"x4\": 266, \"y2\": 558}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 10, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 572, \"x3\": 352, \"y4\": 572, \"x1\": 312, \"y1\": 552, \"x4\": 312, \"y2\": 552}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 398, \"y3\": 572, \"x3\": 398, \"y4\": 572, \"x1\": 358, \"y1\": 550, \"x4\": 358, \"y2\": 550}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 10, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 568, \"x3\": 620, \"y4\": 568, \"x1\": 546, \"y1\": 544, \"x4\": 546, \"y2\": 544}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"18,000\"}], \"category\": \"menu.price\", \"group_id\": 10, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 256, \"y3\": 598, \"x3\": 256, \"y4\": 598, \"x1\": 244, \"y1\": 582, \"x4\": 244, \"y2\": 582}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"1\"}, {\"quad\": {\"x2\": 280, \"y3\": 598, \"x3\": 280, \"y4\": 598, \"x1\": 264, \"y1\": 582, \"x4\": 264, \"y2\": 582}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 11, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 596, \"x3\": 352, \"y4\": 596, \"x1\": 312, \"y1\": 576, \"x4\": 312, \"y2\": 576}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 434, \"y3\": 596, \"x3\": 434, \"y4\": 596, \"x1\": 358, \"y1\": 576, \"x4\": 358, \"y2\": 576}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"Orange\"}], \"category\": \"menu.nm\", \"group_id\": 11, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 594, \"x3\": 620, \"y4\": 594, \"x1\": 544, \"y1\": 570, \"x4\": 544, \"y2\": 570}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"29,000\"}], \"category\": \"menu.price\", \"group_id\": 11, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 258, \"y3\": 622, \"x3\": 258, \"y4\": 622, \"x1\": 246, \"y1\": 606, \"x4\": 246, \"y2\": 606}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"1\"}, {\"quad\": {\"x2\": 282, \"y3\": 622, \"x3\": 282, \"y4\": 622, \"x1\": 268, \"y1\": 608, \"x4\": 268, \"y2\": 608}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 12, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 624, \"x3\": 364, \"y4\": 624, \"x1\": 312, \"y1\": 602, \"x4\": 312, \"y2\": 602}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"Ayam\"}, {\"quad\": {\"x2\": 422, \"y3\": 620, \"x3\": 422, \"y4\": 620, \"x1\": 370, \"y1\": 600, \"x4\": 370, \"y2\": 600}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"Suir\"}, {\"quad\": {\"x2\": 478, \"y3\": 620, \"x3\": 478, \"y4\": 620, \"x1\": 428, \"y1\": 598, \"x4\": 428, \"y2\": 598}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"Bali\"}], \"category\": \"menu.nm\", \"group_id\": 12, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 620, \"x3\": 618, \"y4\": 620, \"x1\": 544, \"y1\": 596, \"x4\": 544, \"y2\": 596}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"85,000\"}], \"category\": \"menu.price\", \"group_id\": 12, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 260, \"y3\": 650, \"x3\": 260, \"y4\": 650, \"x1\": 242, \"y1\": 628, \"x4\": 242, \"y2\": 628}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"2\"}, {\"quad\": {\"x2\": 282, \"y3\": 648, \"x3\": 282, \"y4\": 648, \"x1\": 266, \"y1\": 632, \"x4\": 266, \"y2\": 632}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 13, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 648, \"x3\": 364, \"y4\": 648, \"x1\": 312, \"y1\": 626, \"x4\": 312, \"y2\": 626}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"Tahu\"}, {\"quad\": {\"x2\": 444, \"y3\": 648, \"x3\": 443, \"y4\": 645, \"x1\": 370, \"y1\": 625, \"x4\": 369, \"y2\": 628}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"Goreng\"}], \"category\": \"menu.nm\", \"group_id\": 13, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 619, \"y3\": 644, \"x3\": 620, \"y4\": 647, \"x1\": 543, \"y1\": 622, \"x4\": 544, \"y2\": 619}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"36,000\"}], \"category\": \"menu.price\", \"group_id\": 13, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 260, \"y3\": 674, \"x3\": 260, \"y4\": 674, \"x1\": 242, \"y1\": 654, \"x4\": 242, \"y2\": 654}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"2\"}, {\"quad\": {\"x2\": 284, \"y3\": 674, \"x3\": 284, \"y4\": 674, \"x1\": 268, \"y1\": 660, \"x4\": 268, \"y2\": 660}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 14, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 376, \"y3\": 674, \"x3\": 376, \"y4\": 674, \"x1\": 314, \"y1\": 652, \"x4\": 314, \"y2\": 652}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"Tempe\"}, {\"quad\": {\"x2\": 458, \"y3\": 672, \"x3\": 458, \"y4\": 672, \"x1\": 384, \"y1\": 650, \"x4\": 384, \"y2\": 650}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"Goreng\"}], \"category\": \"menu.nm\", \"group_id\": 14, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 668, \"x3\": 620, \"y4\": 668, \"x1\": 546, \"y1\": 644, \"x4\": 546, \"y2\": 644}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"36,000\"}], \"category\": \"menu.price\", \"group_id\": 14, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 258, \"y3\": 700, \"x3\": 258, \"y4\": 700, \"x1\": 244, \"y1\": 682, \"x4\": 244, \"y2\": 682}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"1\"}, {\"quad\": {\"x2\": 282, \"y3\": 700, \"x3\": 282, \"y4\": 700, \"x1\": 266, \"y1\": 686, \"x4\": 266, \"y2\": 686}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 15, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 698, \"x3\": 364, \"y4\": 698, \"x1\": 312, \"y1\": 676, \"x4\": 312, \"y2\": 676}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"Tahu\"}, {\"quad\": {\"x2\": 434, \"y3\": 696, \"x3\": 434, \"y4\": 696, \"x1\": 370, \"y1\": 674, \"x4\": 370, \"y2\": 674}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"Telor\"}, {\"quad\": {\"x2\": 494, \"y3\": 694, \"x3\": 494, \"y4\": 694, \"x1\": 440, \"y1\": 672, \"x4\": 440, \"y2\": 672}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"Asin\"}], \"category\": \"menu.nm\", \"group_id\": 15, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 630, \"y3\": 690, \"x3\": 630, \"y4\": 690, \"x1\": 548, \"y1\": 668, \"x4\": 548, \"y2\": 668}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"40,000.\"}], \"category\": \"menu.price\", \"group_id\": 15, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 256, \"y3\": 726, \"x3\": 256, \"y4\": 726, \"x1\": 244, \"y1\": 708, \"x4\": 244, \"y2\": 708}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"1\"}, {\"quad\": {\"x2\": 282, \"y3\": 726, \"x3\": 282, \"y4\": 726, \"x1\": 268, \"y1\": 710, \"x4\": 268, \"y2\": 710}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 16, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 724, \"x3\": 364, \"y4\": 724, \"x1\": 312, \"y1\": 702, \"x4\": 312, \"y2\": 702}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"Nasi\"}, {\"quad\": {\"x2\": 446, \"y3\": 722, \"x3\": 446, \"y4\": 722, \"x1\": 372, \"y1\": 700, \"x4\": 372, \"y2\": 700}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"Goreng\"}, {\"quad\": {\"x2\": 505, \"y3\": 715, \"x3\": 506, \"y4\": 718, \"x1\": 453, \"y1\": 696, \"x4\": 454, \"y2\": 693}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"Samb\"}], \"category\": \"menu.nm\", \"group_id\": 16, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 626, \"y3\": 716, \"x3\": 626, \"y4\": 716, \"x1\": 550, \"y1\": 692, \"x4\": 550, \"y2\": 692}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"70,000\"}], \"category\": \"menu.price\", \"group_id\": 16, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 256, \"y3\": 752, \"x3\": 256, \"y4\": 752, \"x1\": 242, \"y1\": 734, \"x4\": 242, \"y2\": 734}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"3\"}, {\"quad\": {\"x2\": 280, \"y3\": 752, \"x3\": 280, \"y4\": 752, \"x1\": 266, \"y1\": 738, \"x4\": 266, \"y2\": 738}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 17, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 750, \"x3\": 352, \"y4\": 750, \"x1\": 312, \"y1\": 728, \"x4\": 312, \"y2\": 728}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"Bbk\"}, {\"quad\": {\"x2\": 457, \"y3\": 747, \"x3\": 458, \"y4\": 749, \"x1\": 357, \"y1\": 726, \"x4\": 358, \"y2\": 723}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"Panggang\"}, {\"quad\": {\"x2\": 508, \"y3\": 742, \"x3\": 508, \"y4\": 742, \"x1\": 466, \"y1\": 722, \"x4\": 466, \"y2\": 722}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"Sam\"}], \"category\": \"menu.nm\", \"group_id\": 17, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 630, \"y3\": 742, \"x3\": 630, \"y4\": 742, \"x1\": 538, \"y1\": 716, \"x4\": 538, \"y2\": 716}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"366,000\"}], \"category\": \"menu.price\", \"group_id\": 17, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 778, \"x3\": 254, \"y4\": 778, \"x1\": 242, \"y1\": 762, \"x4\": 242, \"y2\": 762}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"1\"}, {\"quad\": {\"x2\": 280, \"y3\": 778, \"x3\": 280, \"y4\": 778, \"x1\": 266, \"y1\": 764, \"x4\": 266, \"y2\": 764}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 18, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 778, \"x3\": 364, \"y4\": 778, \"x1\": 312, \"y1\": 754, \"x4\": 312, \"y2\": 754}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"Ayam\"}, {\"quad\": {\"x2\": 447, \"y3\": 771, \"x3\": 448, \"y4\": 774, \"x1\": 371, \"y1\": 750, \"x4\": 372, \"y2\": 747}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"Sambal\"}, {\"quad\": {\"x2\": 508, \"y3\": 772, \"x3\": 508, \"y4\": 772, \"x1\": 454, \"y1\": 746, \"x4\": 454, \"y2\": 746}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"Hija\"}], \"category\": \"menu.nm\", \"group_id\": 18, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 632, \"y3\": 768, \"x3\": 632, \"y4\": 768, \"x1\": 554, \"y1\": 742, \"x4\": 554, \"y2\": 742}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"92,000\"}], \"category\": \"menu.price\", \"group_id\": 18, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 806, \"x3\": 254, \"y4\": 806, \"x1\": 236, \"y1\": 784, \"x4\": 236, \"y2\": 784}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"2\"}, {\"quad\": {\"x2\": 278, \"y3\": 804, \"x3\": 278, \"y4\": 804, \"x1\": 262, \"y1\": 788, \"x4\": 262, \"y2\": 788}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 19, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 802, \"x3\": 352, \"y4\": 802, \"x1\": 310, \"y1\": 780, \"x4\": 310, \"y2\": 780}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"Hot\"}, {\"quad\": {\"x2\": 400, \"y3\": 800, \"x3\": 400, \"y4\": 800, \"x1\": 358, \"y1\": 778, \"x4\": 358, \"y2\": 778}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 19, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 634, \"y3\": 796, \"x3\": 634, \"y4\": 796, \"x1\": 554, \"y1\": 770, \"x4\": 554, \"y2\": 770}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"44,000\"}], \"category\": \"menu.price\", \"group_id\": 19, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 252, \"y3\": 834, \"x3\": 252, \"y4\": 834, \"x1\": 240, \"y1\": 816, \"x4\": 240, \"y2\": 816}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"1\"}, {\"quad\": {\"x2\": 278, \"y3\": 832, \"x3\": 278, \"y4\": 832, \"x1\": 262, \"y1\": 816, \"x4\": 262, \"y2\": 816}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 20, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 830, \"x3\": 352, \"y4\": 830, \"x1\": 312, \"y1\": 808, \"x4\": 312, \"y2\": 808}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 412, \"y3\": 830, \"x3\": 412, \"y4\": 830, \"x1\": 360, \"y1\": 804, \"x4\": 360, \"y2\": 804}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"Kopi\"}], \"category\": \"menu.nm\", \"group_id\": 20, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 636, \"y3\": 826, \"x3\": 636, \"y4\": 826, \"x1\": 556, \"y1\": 798, \"x4\": 556, \"y2\": 798}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"32,000\"}], \"category\": \"menu.price\", \"group_id\": 20, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 862, \"x3\": 250, \"y4\": 862, \"x1\": 238, \"y1\": 844, \"x4\": 238, \"y2\": 844}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 862, \"x3\": 276, \"y4\": 862, \"x1\": 260, \"y1\": 844, \"x4\": 260, \"y2\": 844}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 21, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 860, \"x3\": 364, \"y4\": 860, \"x1\": 310, \"y1\": 836, \"x4\": 310, \"y2\": 836}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"Tahu\"}, {\"quad\": {\"x2\": 438, \"y3\": 858, \"x3\": 438, \"y4\": 858, \"x1\": 372, \"y1\": 834, \"x4\": 372, \"y2\": 834}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"Telor\"}, {\"quad\": {\"x2\": 500, \"y3\": 854, \"x3\": 500, \"y4\": 854, \"x1\": 444, \"y1\": 832, \"x4\": 444, \"y2\": 832}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"Asin\"}], \"category\": \"menu.nm\", \"group_id\": 21, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 638, \"y3\": 854, \"x3\": 638, \"y4\": 854, \"x1\": 558, \"y1\": 826, \"x4\": 558, \"y2\": 826}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"40,000\"}], \"category\": \"menu.price\", \"group_id\": 21, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 892, \"x3\": 250, \"y4\": 892, \"x1\": 238, \"y1\": 872, \"x4\": 238, \"y2\": 872}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 890, \"x3\": 276, \"y4\": 890, \"x1\": 260, \"y1\": 872, \"x4\": 260, \"y2\": 872}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 22, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 888, \"x3\": 364, \"y4\": 888, \"x1\": 310, \"y1\": 866, \"x4\": 310, \"y2\": 866}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"Free\"}, {\"quad\": {\"x2\": 414, \"y3\": 886, \"x3\": 414, \"y4\": 886, \"x1\": 374, \"y1\": 864, \"x4\": 374, \"y2\": 864}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 464, \"y3\": 884, \"x3\": 464, \"y4\": 884, \"x1\": 422, \"y1\": 862, \"x4\": 422, \"y2\": 862}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 22, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 640, \"y3\": 878, \"x3\": 640, \"y4\": 878, \"x1\": 622, \"y1\": 856, \"x4\": 622, \"y2\": 856}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"0\"}], \"category\": \"menu.price\", \"group_id\": 22, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 920, \"x3\": 250, \"y4\": 920, \"x1\": 236, \"y1\": 900, \"x4\": 236, \"y2\": 900}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 920, \"x3\": 276, \"y4\": 920, \"x1\": 260, \"y1\": 902, \"x4\": 260, \"y2\": 902}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 23, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 376, \"y3\": 916, \"x3\": 376, \"y4\": 916, \"x1\": 308, \"y1\": 892, \"x4\": 308, \"y2\": 892}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"Bebek\"}, {\"quad\": {\"x2\": 464, \"y3\": 914, \"x3\": 464, \"y4\": 914, \"x1\": 384, \"y1\": 890, \"x4\": 384, \"y2\": 890}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"Street\"}], \"category\": \"menu.nm\", \"group_id\": 23, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 641, \"y3\": 908, \"x3\": 642, \"y4\": 911, \"x1\": 559, \"y1\": 884, \"x4\": 560, \"y2\": 881}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"44,000\"}], \"category\": \"menu.price\", \"group_id\": 23, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 948, \"x3\": 250, \"y4\": 948, \"x1\": 238, \"y1\": 930, \"x4\": 238, \"y2\": 930}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 946, \"x3\": 276, \"y4\": 946, \"x1\": 260, \"y1\": 930, \"x4\": 260, \"y2\": 930}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 24, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 946, \"x3\": 352, \"y4\": 946, \"x1\": 312, \"y1\": 924, \"x4\": 312, \"y2\": 924}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 402, \"y3\": 944, \"x3\": 402, \"y4\": 944, \"x1\": 360, \"y1\": 922, \"x4\": 360, \"y2\": 922}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"Tea\"}, {\"quad\": {\"x2\": 480, \"y3\": 942, \"x3\": 480, \"y4\": 942, \"x1\": 412, \"y1\": 920, \"x4\": 412, \"y2\": 920}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"Tawar\"}], \"category\": \"menu.nm\", \"group_id\": 24, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 642, \"y3\": 938, \"x3\": 642, \"y4\": 938, \"x1\": 564, \"y1\": 912, \"x4\": 564, \"y2\": 912}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"18,000\"}], \"category\": \"menu.price\", \"group_id\": 24, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 479, \"y3\": 998, \"x3\": 481, \"y4\": 1005, \"x1\": 360, \"y1\": 979, \"x4\": 362, \"y2\": 973}, \"is_key\": 1, \"row_id\": 2179915, \"text\": \"Sub-Total\"}, {\"quad\": {\"x2\": 645, \"y3\": 995, \"x3\": 646, \"y4\": 998, \"x1\": 527, \"y1\": 970, \"x4\": 528, \"y2\": 967}, \"is_key\": 0, \"row_id\": 2179915, \"text\": \"1,346,000\"}], \"category\": \"sub_total.subtotal_price\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 481, \"y3\": 1027, \"x3\": 482, \"y4\": 1030, \"x1\": 387, \"y1\": 1007, \"x4\": 388, \"y2\": 1004}, \"is_key\": 1, \"row_id\": 2179916, \"text\": \"Service\"}, {\"quad\": {\"x2\": 646, \"y3\": 1026, \"x3\": 646, \"y4\": 1026, \"x1\": 554, \"y1\": 998, \"x4\": 554, \"y2\": 998}, \"is_key\": 0, \"row_id\": 2179916, \"text\": \"100,950\"}], \"category\": \"sub_total.service_price\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 482, \"y3\": 1056, \"x3\": 482, \"y4\": 1056, \"x1\": 438, \"y1\": 1032, \"x4\": 438, \"y2\": 1032}, \"is_key\": 1, \"row_id\": 2179917, \"text\": \"PB1\"}, {\"quad\": {\"x2\": 648, \"y3\": 1052, \"x3\": 648, \"y4\": 1052, \"x1\": 556, \"y1\": 1026, \"x4\": 556, \"y2\": 1026}, \"is_key\": 0, \"row_id\": 2179917, \"text\": \"144,695\"}], \"category\": \"sub_total.tax_price\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 481, \"y3\": 1085, \"x3\": 482, \"y4\": 1088, \"x1\": 375, \"y1\": 1063, \"x4\": 376, \"y2\": 1061}, \"is_key\": 1, \"row_id\": 2179918, \"text\": \"Rounding\"}, {\"quad\": {\"x2\": 648, \"y3\": 1078, \"x3\": 648, \"y4\": 1078, \"x1\": 606, \"y1\": 1054, \"x4\": 606, \"y2\": 1054}, \"is_key\": 0, \"row_id\": 2179918, \"text\": \"-45\"}], \"category\": \"sub_total.etc\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 334, \"y3\": 1162, \"x3\": 334, \"y4\": 1162, \"x1\": 266, \"y1\": 1142, \"x4\": 266, \"y2\": 1142}, \"is_key\": 1, \"row_id\": 2179919, \"text\": \"Grand\"}, {\"quad\": {\"x2\": 408, \"y3\": 1160, \"x3\": 408, \"y4\": 1160, \"x1\": 340, \"y1\": 1138, \"x4\": 340, \"y2\": 1138}, \"is_key\": 1, \"row_id\": 2179919, \"text\": \"Total\"}, {\"quad\": {\"x2\": 647, \"y3\": 1153, \"x3\": 649, \"y4\": 1161, \"x1\": 418, \"y1\": 1117, \"x4\": 420, \"y2\": 1108}, \"is_key\": 0, \"row_id\": 2179919, \"text\": \"1,591,600\"}], \"category\": \"total.total_price\", \"group_id\": 26, \"sub_group_id\": 0}], \"roi\": {}, \"repeating_symbol\": [], \"dontcare\": []}\n"
+          ]
+        }
+      ],
+      "source": [
+        "# let's load the corresponding JSON dictionary (as string representation)\n",
+        "ground_truth = example['ground_truth']\n",
+        "print(ground_truth)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "8V8Rgq4jwoqL"
+      },
+      "source": [
+        "We can also parse the string as a Python dictionary using `ast.literal_eval`. Each training example has a single \"gt_parse\" key, which contains the ground truth parsing of the document:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "0iODZViTwqVf",
+        "outputId": "9e269cf8-79d1-4660-9254-10a5a25c61bf"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "{'menu': [{'nm': 'Nasi Campur Bali', 'cnt': '1 x', 'price': '75,000'},\n",
+              "  {'nm': 'Bbk Bengil Nasi', 'cnt': '1 x', 'price': '125,000'},\n",
+              "  {'nm': 'MilkShake Starwb', 'cnt': '1 x', 'price': '37,000'},\n",
+              "  {'nm': 'Ice Lemon Tea', 'cnt': '1 x', 'price': '24,000'},\n",
+              "  {'nm': 'Nasi Ayam Dewata', 'cnt': '1 x', 'price': '70,000'},\n",
+              "  {'nm': 'Free Ice Tea', 'cnt': '3 x', 'price': '0'},\n",
+              "  {'nm': 'Organic Green Sa', 'cnt': '1 x', 'price': '65,000'},\n",
+              "  {'nm': 'Ice Tea', 'cnt': '1 x', 'price': '18,000'},\n",
+              "  {'nm': 'Ice Orange', 'cnt': '1 x', 'price': '29,000'},\n",
+              "  {'nm': 'Ayam Suir Bali', 'cnt': '1 x', 'price': '85,000'},\n",
+              "  {'nm': 'Tahu Goreng', 'cnt': '2 x', 'price': '36,000'},\n",
+              "  {'nm': 'Tempe Goreng', 'cnt': '2 x', 'price': '36,000'},\n",
+              "  {'nm': 'Tahu Telor Asin', 'cnt': '1 x', 'price': '40,000.'},\n",
+              "  {'nm': 'Nasi Goreng Samb', 'cnt': '1 x', 'price': '70,000'},\n",
+              "  {'nm': 'Bbk Panggang Sam', 'cnt': '3 x', 'price': '366,000'},\n",
+              "  {'nm': 'Ayam Sambal Hija', 'cnt': '1 x', 'price': '92,000'},\n",
+              "  {'nm': 'Hot Tea', 'cnt': '2 x', 'price': '44,000'},\n",
+              "  {'nm': 'Ice Kopi', 'cnt': '1 x', 'price': '32,000'},\n",
+              "  {'nm': 'Tahu Telor Asin', 'cnt': '1 x', 'price': '40,000'},\n",
+              "  {'nm': 'Free Ice Tea', 'cnt': '1 x', 'price': '0'},\n",
+              "  {'nm': 'Bebek Street', 'cnt': '1 x', 'price': '44,000'},\n",
+              "  {'nm': 'Ice Tea Tawar', 'cnt': '1 x', 'price': '18,000'}],\n",
+              " 'sub_total': {'subtotal_price': '1,346,000',\n",
+              "  'service_price': '100,950',\n",
+              "  'tax_price': '144,695',\n",
+              "  'etc': '-45'},\n",
+              " 'total': {'total_price': '1,591,600'}}"
+            ]
+          },
+          "execution_count": 5,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "from ast import literal_eval\n",
+        "\n",
+        "literal_eval(ground_truth)['gt_parse']"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "BCjMK93Cz3zf"
+      },
+      "source": [
+        "## Load model and processor\n",
+        "\n",
+        "Next, we load the model (Donut is an instance of [VisionEncoderDecoderModel](https://huggingface.co/docs/transformers/model_doc/vision-encoder-decoder)), and the processor, which is the object that can be used to prepare inputs for the model.\n",
+        "\n",
+        "We'll update some settings for fine-tuning, namely the image size and the max length of the decoder."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 49,
+          "referenced_widgets": [
+            "ddd6a6f26e4a40de85db830c02834c4c",
+            "646592d608724342ad765c7e7457740d",
+            "c46ec088b99646f091f934536af46d5e",
+            "3ce6f898ce604f258efab30dd9f65b79",
+            "38fff333701c4678b5c69863aa8992ac",
+            "2472d601c42041e6acb51d19de547a0a",
+            "59585c4440a64e1fb76601df8aee255d",
+            "2a459b1c958240d89f753fe695b457e0",
+            "7939062da2ee4ebabadb0a5f06ee3276",
+            "ac08a565f2d5447a95d2e6af307f3f09",
+            "4ed83abdd375497f9edb35c828d70be7"
+          ]
+        },
+        "id": "ahkkeo8_o69z",
+        "outputId": "ea22fae8-ca64-49d1-c886-046140d0d2a1"
+      },
+      "outputs": [],
+      "source": [
+        "from transformers import VisionEncoderDecoderConfig\n",
+        "\n",
+        "image_size = [1280, 960]\n",
+        "max_length = 768\n",
+        "\n",
+        "# update image_size of the encoder\n",
+        "# during pre-training, a larger image size was used\n",
+        "config = VisionEncoderDecoderConfig.from_pretrained(\"naver-clova-ix/donut-base\")\n",
+        "config.encoder.image_size = image_size # (height, width)\n",
+        "# update max_length of the decoder (for generation)\n",
+        "config.decoder.max_length = max_length\n",
+        "# TODO we should actually update max_position_embeddings and interpolate the pre-trained ones:\n",
+        "# https://github.com/clovaai/donut/blob/0acc65a85d140852b8d9928565f0f6b2d98dc088/donut/model.py#L602"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "MUiQda9_mjAC"
+      },
+      "source": [
+        "Next, we instantiate the model with our custom config, as well as the processor. Make sure that all pre-trained weights are correctly loaded (a warning would tell you if that's not the case)."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 7,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 279,
+          "referenced_widgets": [
+            "f0e0d969d5f943c3ac158a6a443bceee",
+            "c21173370f63409b84b9f40abc202efd",
+            "cd63bf0c96b6466586c66240f67b35a5",
+            "ab6b00b5c38d40e4878e5de67bba6b95",
+            "0f2dc68b57614e79b95ddeb715f124af",
+            "2781fb98daf147638db891d565d2f194",
+            "da910c9d7bc94d6fabe99bfcd626d9a2",
+            "5b515a9e88074259b1067880ad7aa637",
+            "6dd394d212694b969b540123f515957a",
+            "262f11dfba44467c882893cec6523189",
+            "3e8e09b6655a4c8fb3995915a69c795f",
+            "0c565bd0bd89433286f309c0a728e020",
+            "9ab3a07b87854294b687ab1bd1ce2fe1",
+            "61c95b7243604620a9151ce8b6fcc910",
+            "f21af123c24f43498942dd4f3e91c54f",
+            "f6c554c9119f4152bd747905b3b2ade3",
+            "45c29055f8a74361b562fb2baaa3b71f",
+            "731ee8128e584ddcbe117dd03612467d",
+            "d68dcd34129d4922b23a3bc96739814f",
+            "2e682e41d92343b792991eaa2b72d7de",
+            "c6656f51d29747c7a831f8b4739b8cd7",
+            "ed98bdb5c8364a6782a1883411acd5f5",
+            "def152f1a9e84c7e90e6e24f001f29a2",
+            "140f7d5cb0fb4b4b8598d1552a429052",
+            "ad391511f2ec4e3ebb69865afee7ae6b",
+            "c5083eb93376434e9a53fc44d7d215b9",
+            "56fea1b142db47fbab0b118185587e76",
+            "a4eacb994f2147d29d2d68e9b3c456aa",
+            "205926dbd19445c08bd1b8a02e33634f",
+            "9479170c55a34e5a9ccce3115f01b68e",
+            "0fedf481a76a4d319ddc6afe51345a36",
+            "394b5ca6361e4d38ba6cca638de5cdcb",
+            "7b2f94dc358c4e5cb6662463e771bb2d",
+            "efbbbb45e1554253bbf331525f219e4c",
+            "ab1c3ba6663a40c383a57333f5b13ddb",
+            "4664a4a1ab034098a12b6ad238c0391b",
+            "257fa5076dd74486b7751bffa39c2ef8",
+            "b02d03f2ac8d47559d03eb83a01d467e",
+            "3612afa317c5414bbffdbc1f241eb133",
+            "ca6747f101dc44fa8d3b85f668fff5ed",
+            "f8c2d38923c948cf8f2cf8c49ffb2c8d",
+            "37c969be0a7946c6a7d45940fcde5cf9",
+            "b3a98298b4ea434da0d8815ba0f2c4a4",
+            "e6523a394c4442bd949cae3f7666b6d4",
+            "9a45e993bffc469a8a156cba70774d25",
+            "82f65ddff78c4c528169704a78d6d9f5",
+            "7bd828ddfe814d05a62736a9d91a8272",
+            "9da3a58c74e64d4d8e39921e472fb6ea",
+            "c253f1450fdc49939ad663b6f98b6929",
+            "4f2be832c1f04902af8bfc4f5d971057",
+            "dda5061d7d3d4a2cb166bb9473dc3fbb",
+            "d3ff6bc3da3b4754af245dcbacd0914c",
+            "87407d9ae1f54c3c8383e2934aef15b4",
+            "617aea856f93495d9f56dfc83a33d4bb",
+            "23e4cf09102a4753844ceed08a211d53",
+            "9bce140411404cad931ec4022a76989e",
+            "50ce7fc092624343a610286377ecd39a",
+            "b28110567ad04fdeafea8f405f71e7ef",
+            "f578278adfb146e8bdf89810a39d43cb",
+            "fbed03f8b8ad47638a418b9f423e4c26",
+            "840a81ea307a4633bfd9846f89121257",
+            "7a2a38deff05410b92c7f0aca5e2f906",
+            "690c1c1fdb98452ea766955c7a4966be",
+            "c08e405d7915496089723b6d5e78d163",
+            "8f12f7c6ea604de7ab155971ffea8275",
+            "165a9c0135cb45869feb49beacb8101a",
+            "2ca98f8a45fb4335ac197e9b7c019e41",
+            "6d146fd4003e47978a253192463dd514",
+            "33596291f0c344ad9219c9a7eb6c5c90",
+            "30374f50d4af4b9598cb13823ad7780c",
+            "6c9cca8ae41441b29f2dd7ac81cd35d4",
+            "9525813936a14ac49a7ca525a411c2f9",
+            "6a6be6466e6a4814870c38d55279e1c1",
+            "fe5fe724aaa14f2bb80e84fc589103fc",
+            "c65a6cc99b06467cbc7f4efe8d80aae0",
+            "6a3d2f0a94ea4f72bc81400880f8c430",
+            "c3735a62d26743cc88f0bb71712edaa2"
+          ]
+        },
+        "id": "84TkZP5zz4hE",
+        "outputId": "9d49492d-5b3f-41b1-88a6-4c8a85e3cdd3"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "2024-04-30 11:46:46.237889: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+            "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+            "2024-04-30 11:46:46.861365: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
+            "Could not find image processor class in the image processor config or the model config. Loading based on pattern matching with the model's feature extractor configuration. Please open a PR/issue to update `preprocessor_config.json` to use `image_processor_type` instead of `feature_extractor_type`. This warning will be removed in v4.40.\n"
+          ]
+        }
+      ],
+      "source": [
+        "from transformers import DonutProcessor, VisionEncoderDecoderModel\n",
+        "\n",
+        "processor = DonutProcessor.from_pretrained(\"naver-clova-ix/donut-base\")\n",
+        "model = VisionEncoderDecoderModel.from_pretrained(\"naver-clova-ix/donut-base\", config=config)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "b46s3KR-x8Iv"
+      },
+      "source": [
+        "## Create PyTorch dataset\n",
+        "\n",
+        "Here we create a regular PyTorch dataset.\n",
+        "\n",
+        "The model doesn't directly take the (image, JSON) pairs as input and labels. Rather, we create `pixel_values` and `labels`. Both are PyTorch tensors. The `pixel_values` are the input images (resized, padded and normalized), and the `labels` are the `input_ids` of the target sequence (which is a flattened version of the JSON), with padding tokens replaced by -100 (to make sure these are ignored by the loss function). Both are created using `DonutProcessor` (which internally combines an image processor, for the image modality, and a tokenizer, for the text modality).\n",
+        "\n",
+        "Note that we're also adding tokens to the vocabulary of the decoder (and corresponding tokenizer) for all keys of the dictionaries in our dataset, like \"\\<s_menu>\". This makes sure the model learns an embedding vector for them. Without doing this, some keys might get split up into multiple subword tokens, in which case the model just learns an embedding for the subword tokens, rather than a direct embedding for these keys."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "metadata": {
+        "id": "7tWX_qJDvw_S"
+      },
+      "outputs": [],
+      "source": [
+        "import json\n",
+        "import random\n",
+        "from typing import Any, List, Tuple\n",
+        "\n",
+        "import torch\n",
+        "from torch.utils.data import Dataset\n",
+        "\n",
+        "added_tokens = []\n",
+        "\n",
+        "class DonutDataset(Dataset):\n",
+        "    \"\"\"\n",
+        "    PyTorch Dataset for Donut. This class takes a HuggingFace Dataset as input.\n",
+        "    \n",
+        "    Each row, consists of image path(png/jpg/jpeg) and gt data (json/jsonl/txt),\n",
+        "    and it will be converted into pixel_values (vectorized image) and labels (input_ids of the tokenized string).\n",
+        "    \n",
+        "    Args:\n",
+        "        dataset_name_or_path: name of dataset (available at huggingface.co/datasets) or the path containing image files and metadata.jsonl\n",
+        "        max_length: the max number of tokens for the target sequences\n",
+        "        split: whether to load \"train\", \"validation\" or \"test\" split\n",
+        "        ignore_id: ignore_index for torch.nn.CrossEntropyLoss\n",
+        "        task_start_token: the special token to be fed to the decoder to conduct the target task\n",
+        "        prompt_end_token: the special token at the end of the sequences\n",
+        "        sort_json_key: whether or not to sort the JSON keys\n",
+        "    \"\"\"\n",
+        "\n",
+        "    def __init__(\n",
+        "        self,\n",
+        "        dataset_name_or_path: str,\n",
+        "        max_length: int,\n",
+        "        split: str = \"train\",\n",
+        "        ignore_id: int = -100,\n",
+        "        task_start_token: str = \"<s>\",\n",
+        "        prompt_end_token: str = None,\n",
+        "        sort_json_key: bool = True,\n",
+        "    ):\n",
+        "        super().__init__()\n",
+        "\n",
+        "        self.max_length = max_length\n",
+        "        self.split = split\n",
+        "        self.ignore_id = ignore_id\n",
+        "        self.task_start_token = task_start_token\n",
+        "        self.prompt_end_token = prompt_end_token if prompt_end_token else task_start_token\n",
+        "        self.sort_json_key = sort_json_key\n",
+        "\n",
+        "        self.dataset = load_dataset(dataset_name_or_path, split=self.split)\n",
+        "        self.dataset_length = len(self.dataset)\n",
+        "\n",
+        "        self.gt_token_sequences = []\n",
+        "        for sample in self.dataset:\n",
+        "            ground_truth = json.loads(sample[\"ground_truth\"])\n",
+        "            if \"gt_parses\" in ground_truth:  # when multiple ground truths are available, e.g., docvqa\n",
+        "                assert isinstance(ground_truth[\"gt_parses\"], list)\n",
+        "                gt_jsons = ground_truth[\"gt_parses\"]\n",
+        "            else:\n",
+        "                assert \"gt_parse\" in ground_truth and isinstance(ground_truth[\"gt_parse\"], dict)\n",
+        "                gt_jsons = [ground_truth[\"gt_parse\"]]\n",
+        "\n",
+        "            self.gt_token_sequences.append(\n",
+        "                [\n",
+        "                    self.json2token(\n",
+        "                        gt_json,\n",
+        "                        update_special_tokens_for_json_key=self.split == \"train\",\n",
+        "                        sort_json_key=self.sort_json_key,\n",
+        "                    )\n",
+        "                    + processor.tokenizer.eos_token\n",
+        "                    for gt_json in gt_jsons  # load json from list of json\n",
+        "                ]\n",
+        "            )\n",
+        "\n",
+        "        self.add_tokens([self.task_start_token, self.prompt_end_token])\n",
+        "        self.prompt_end_token_id = processor.tokenizer.convert_tokens_to_ids(self.prompt_end_token)\n",
+        "\n",
+        "    def json2token(self, obj: Any, update_special_tokens_for_json_key: bool = True, sort_json_key: bool = True):\n",
+        "        \"\"\"\n",
+        "        Convert an ordered JSON object into a token sequence\n",
+        "        \"\"\"\n",
+        "        if type(obj) == dict:\n",
+        "            if len(obj) == 1 and \"text_sequence\" in obj:\n",
+        "                return obj[\"text_sequence\"]\n",
+        "            else:\n",
+        "                output = \"\"\n",
+        "                if sort_json_key:\n",
+        "                    keys = sorted(obj.keys(), reverse=True)\n",
+        "                else:\n",
+        "                    keys = obj.keys()\n",
+        "                for k in keys:\n",
+        "                    if update_special_tokens_for_json_key:\n",
+        "                        self.add_tokens([fr\"<s_{k}>\", fr\"</s_{k}>\"])\n",
+        "                    output += (\n",
+        "                        fr\"<s_{k}>\"\n",
+        "                        + self.json2token(obj[k], update_special_tokens_for_json_key, sort_json_key)\n",
+        "                        + fr\"</s_{k}>\"\n",
+        "                    )\n",
+        "                return output\n",
+        "        elif type(obj) == list:\n",
+        "            return r\"<sep/>\".join(\n",
+        "                [self.json2token(item, update_special_tokens_for_json_key, sort_json_key) for item in obj]\n",
+        "            )\n",
+        "        else:\n",
+        "            obj = str(obj)\n",
+        "            if f\"<{obj}/>\" in added_tokens:\n",
+        "                obj = f\"<{obj}/>\"  # for categorical special tokens\n",
+        "            return obj\n",
+        "    \n",
+        "    def add_tokens(self, list_of_tokens: List[str]):\n",
+        "        \"\"\"\n",
+        "        Add special tokens to tokenizer and resize the token embeddings of the decoder\n",
+        "        \"\"\"\n",
+        "        newly_added_num = processor.tokenizer.add_tokens(list_of_tokens)\n",
+        "        if newly_added_num > 0:\n",
+        "            model.decoder.resize_token_embeddings(len(processor.tokenizer))\n",
+        "            added_tokens.extend(list_of_tokens)\n",
+        "    \n",
+        "    def __len__(self) -> int:\n",
+        "        return self.dataset_length\n",
+        "\n",
+        "    def __getitem__(self, idx: int) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:\n",
+        "        \"\"\"\n",
+        "        Load image from image_path of given dataset_path and convert into input_tensor and labels\n",
+        "        Convert gt data into input_ids (tokenized string)\n",
+        "        Returns:\n",
+        "            input_tensor : preprocessed image\n",
+        "            input_ids : tokenized gt_data\n",
+        "            labels : masked labels (model doesn't need to predict prompt and pad token)\n",
+        "        \"\"\"\n",
+        "        sample = self.dataset[idx]\n",
+        "\n",
+        "        # inputs\n",
+        "        pixel_values = processor(sample[\"image\"], random_padding=self.split == \"train\", return_tensors=\"pt\").pixel_values\n",
+        "        pixel_values = pixel_values.squeeze()\n",
+        "\n",
+        "        # targets\n",
+        "        target_sequence = random.choice(self.gt_token_sequences[idx])  # can be more than one, e.g., DocVQA Task 1\n",
+        "        input_ids = processor.tokenizer(\n",
+        "            target_sequence,\n",
+        "            add_special_tokens=False,\n",
+        "            max_length=self.max_length,\n",
+        "            padding=\"max_length\",\n",
+        "            truncation=True,\n",
+        "            return_tensors=\"pt\",\n",
+        "        )[\"input_ids\"].squeeze(0)\n",
+        "\n",
+        "        labels = input_ids.clone()\n",
+        "        labels[labels == processor.tokenizer.pad_token_id] = self.ignore_id  # model doesn't need to predict pad token\n",
+        "        # labels[: torch.nonzero(labels == self.prompt_end_token_id).sum() + 1] = self.ignore_id  # model doesn't need to predict prompt (for VQA)\n",
+        "        return pixel_values, labels, target_sequence"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "KBseZac0m_W8"
+      },
+      "source": [
+        "Next, we instantiate the datasets:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "3JpazNkf8CnA",
+        "outputId": "2532ee02-08cb-4e10-cf61-87e9c28ba46d"
+      },
+      "outputs": [],
+      "source": [
+        "# we update some settings which differ from pretraining; namely the size of the images + no rotation required\n",
+        "# source: https://github.com/clovaai/donut/blob/master/config/train_cord.yaml\n",
+        "processor.image_processor.size = image_size[::-1] # should be (width, height)\n",
+        "processor.image_processor.do_align_long_axis = False\n",
+        "\n",
+        "train_dataset = DonutDataset(\"naver-clova-ix/cord-v2\", max_length=max_length,\n",
+        "                             split=\"train\", task_start_token=\"<s_cord-v2>\", prompt_end_token=\"<s_cord-v2>\",\n",
+        "                             sort_json_key=False, # cord dataset is preprocessed, so no need for this\n",
+        "                             )\n",
+        "\n",
+        "val_dataset = DonutDataset(\"naver-clova-ix/cord-v2\", max_length=max_length,\n",
+        "                             split=\"validation\", task_start_token=\"<s_cord-v2>\", prompt_end_token=\"<s_cord-v2>\",\n",
+        "                             sort_json_key=False, # cord dataset is preprocessed, so no need for this\n",
+        "                             )"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "QWYmtYxIoHnX"
+      },
+      "source": [
+        "Let's check which tokens are added:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "IfvtQVenFIy1",
+        "outputId": "d3abb09b-2baa-49c2-8332-43849a78745f"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "56"
+            ]
+          },
+          "execution_count": 10,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "len(added_tokens)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "E2hTrsrCB1rp",
+        "outputId": "e3d6601f-2d2d-4a11-8399-e4cf4ea41c3b"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "['<s_menu>', '</s_menu>', '<s_nm>', '</s_nm>', '<s_cnt>', '</s_cnt>', '<s_price>', '</s_price>', '<s_sub_total>', '</s_sub_total>', '<s_subtotal_price>', '</s_subtotal_price>', '<s_service_price>', '</s_service_price>', '<s_tax_price>', '</s_tax_price>', '<s_etc>', '</s_etc>', '<s_total>', '</s_total>', '<s_total_price>', '</s_total_price>', '<s_sub>', '</s_sub>', '<s_cashprice>', '</s_cashprice>', '<s_changeprice>', '</s_changeprice>', '<s_menutype_cnt>', '</s_menutype_cnt>', '<s_menuqty_cnt>', '</s_menuqty_cnt>', '<s_discount_price>', '</s_discount_price>', '<s_unitprice>', '</s_unitprice>', '<s_total_etc>', '</s_total_etc>', '<s_creditcardprice>', '</s_creditcardprice>', '<s_num>', '</s_num>', '<s_discountprice>', '</s_discountprice>', '<s_emoneyprice>', '</s_emoneyprice>', '<s_void_menu>', '</s_void_menu>', '<s_othersvc_price>', '</s_othersvc_price>', '<s_vatyn>', '</s_vatyn>', '<s_itemsubtotal>', '</s_itemsubtotal>', '<s_cord-v2>', '<s_cord-v2>']\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(added_tokens)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "W0Z9JhK3E7WR",
+        "outputId": "2873d2fb-bf4f-4f94-8175-1a1dddaba4d1"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Original number of tokens: 57522\n",
+            "Number of tokens after adding special tokens: 57580\n"
+          ]
+        }
+      ],
+      "source": [
+        "# the vocab size attribute stays constants (might be a bit unintuitive - but doesn't include special tokens)\n",
+        "print(\"Original number of tokens:\", processor.tokenizer.vocab_size)\n",
+        "print(\"Number of tokens after adding special tokens:\", len(processor.tokenizer))"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "tPnYfnwYoMHB"
+      },
+      "source": [
+        "You can verify that a token like `</s_unitprice>` was added to the vocabulary of the tokenizer (and the model):"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 13,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "id": "OLySqOmgE_QC",
+        "outputId": "ab70eb94-9414-43fa-e3e1-c454b45f11e4"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "'</s_unitprice>'"
+            ]
+          },
+          "execution_count": 13,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "processor.decode([57560])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "bd5mNnuPqUAN"
+      },
+      "source": [
+        "As always, it's very important to verify whether our data is prepared correctly. Let's check the first training example:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "metadata": {
+        "id": "mkHzamYl90we"
+      },
+      "outputs": [],
+      "source": [
+        "pixel_values, labels, target_sequence = train_dataset[0]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "07bHWGlFtpIg"
+      },
+      "source": [
+        "This returns the `pixel_values` (the image, but prepared for the model as a PyTorch tensor), the `labels` (which are the encoded `input_ids` of the target sequence, which we want Donut to learn to generate) and the original `target_sequence`. The reason we also return the latter is because this will allow us to compute metrics between the generated sequences and the ground truth target sequences."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 15,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "kNyN_Af0-QMA",
+        "outputId": "6e255ca3-6e8d-47a0-9599-2cd5faf53231"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "torch.Size([3, 1280, 960])\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(pixel_values.shape)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 16,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "uvrqeUmwcNY0",
+        "outputId": "2e049f5b-60d3-48b8-8656-247290172a10"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "<s_menu>\n",
+            "<s_nm>\n",
+            "Nasi\n",
+            "Camp\n",
+            "ur\n",
+            "Bali\n",
+            "</s_nm>\n",
+            "<s_cnt>\n",
+            "1\n",
+            "x\n",
+            "</s_cnt>\n",
+            "<s_price>\n",
+            "7\n",
+            "5,000\n",
+            "</s_price>\n",
+            "<sep/>\n",
+            "<s_nm>\n",
+            "B\n",
+            "b\n",
+            "k\n",
+            "Ben\n",
+            "gil\n",
+            "Nasi\n",
+            "</s_nm>\n",
+            "<s_cnt>\n",
+            "1\n",
+            "x\n",
+            "</s_cnt>\n",
+            "<s_price>\n",
+            "12\n"
+          ]
+        }
+      ],
+      "source": [
+        "# let's print the labels (the first 30 token ID's)\n",
+        "for id in labels.tolist()[:30]:\n",
+        "  if id != -100:\n",
+        "    print(processor.decode([id]))\n",
+        "  else:\n",
+        "    print(id)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 17,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "cwCgvma4z_kp",
+        "outputId": "a94a538c-199a-4e4e-cc85-5935292d9964"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "<s_menu><s_nm>Nasi Campur Bali</s_nm><s_cnt>1 x</s_cnt><s_price>75,000</s_price><sep/><s_nm>Bbk Bengil Nasi</s_nm><s_cnt>1 x</s_cnt><s_price>125,000</s_price><sep/><s_nm>MilkShake Starwb</s_nm><s_cnt>1 x</s_cnt><s_price>37,000</s_price><sep/><s_nm>Ice Lemon Tea</s_nm><s_cnt>1 x</s_cnt><s_price>24,000</s_price><sep/><s_nm>Nasi Ayam Dewata</s_nm><s_cnt>1 x</s_cnt><s_price>70,000</s_price><sep/><s_nm>Free Ice Tea</s_nm><s_cnt>3 x</s_cnt><s_price>0</s_price><sep/><s_nm>Organic Green Sa</s_nm><s_cnt>1 x</s_cnt><s_price>65,000</s_price><sep/><s_nm>Ice Tea</s_nm><s_cnt>1 x</s_cnt><s_price>18,000</s_price><sep/><s_nm>Ice Orange</s_nm><s_cnt>1 x</s_cnt><s_price>29,000</s_price><sep/><s_nm>Ayam Suir Bali</s_nm><s_cnt>1 x</s_cnt><s_price>85,000</s_price><sep/><s_nm>Tahu Goreng</s_nm><s_cnt>2 x</s_cnt><s_price>36,000</s_price><sep/><s_nm>Tempe Goreng</s_nm><s_cnt>2 x</s_cnt><s_price>36,000</s_price><sep/><s_nm>Tahu Telor Asin</s_nm><s_cnt>1 x</s_cnt><s_price>40,000.</s_price><sep/><s_nm>Nasi Goreng Samb</s_nm><s_cnt>1 x</s_cnt><s_price>70,000</s_price><sep/><s_nm>Bbk Panggang Sam</s_nm><s_cnt>3 x</s_cnt><s_price>366,000</s_price><sep/><s_nm>Ayam Sambal Hija</s_nm><s_cnt>1 x</s_cnt><s_price>92,000</s_price><sep/><s_nm>Hot Tea</s_nm><s_cnt>2 x</s_cnt><s_price>44,000</s_price><sep/><s_nm>Ice Kopi</s_nm><s_cnt>1 x</s_cnt><s_price>32,000</s_price><sep/><s_nm>Tahu Telor Asin</s_nm><s_cnt>1 x</s_cnt><s_price>40,000</s_price><sep/><s_nm>Free Ice Tea</s_nm><s_cnt>1 x</s_cnt><s_price>0</s_price><sep/><s_nm>Bebek Street</s_nm><s_cnt>1 x</s_cnt><s_price>44,000</s_price><sep/><s_nm>Ice Tea Tawar</s_nm><s_cnt>1 x</s_cnt><s_price>18,000</s_price></s_menu><s_sub_total><s_subtotal_price>1,346,000</s_subtotal_price><s_service_price>100,950</s_service_price><s_tax_price>144,695</s_tax_price><s_etc>-45</s_etc></s_sub_total><s_total><s_total_price>1,591,600</s_total_price></s_total></s>\n"
+          ]
+        }
+      ],
+      "source": [
+        "# let's check the corresponding target sequence, as a string\n",
+        "print(target_sequence)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "poYwvFdAdikM"
+      },
+      "source": [
+        "Another important thing is that we need to set 2 additional attributes in the configuration of the model. This is not required, but will allow us to train the model by only providing the decoder targets, without having to provide any decoder inputs.\n",
+        "\n",
+        "The model will automatically create the `decoder_input_ids` (the decoder inputs) based on the `labels`, by shifting them one position to the right and prepending the decoder_start_token_id. I recommend checking [this video](https://www.youtube.com/watch?v=IGu7ivuy1Ag&t=888s&ab_channel=NielsRogge) if you want to understand how models like Donut automatically create decoder_input_ids - and more broadly how Donut works."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {
+        "id": "VgRLEVMdc1lx"
+      },
+      "outputs": [],
+      "source": [
+        "model.config.pad_token_id = processor.tokenizer.pad_token_id\n",
+        "model.config.decoder_start_token_id = processor.tokenizer.convert_tokens_to_ids(['<s_cord-v2>'])[0]"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 19,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "bTn0nmssdRWE",
+        "outputId": "9532a846-7b7f-4214-860a-c2d85ca739a3"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Pad token ID: <pad>\n",
+            "Decoder start token ID: <s_cord-v2>\n"
+          ]
+        }
+      ],
+      "source": [
+        "# sanity check\n",
+        "print(\"Pad token ID:\", processor.decode([model.config.pad_token_id]))\n",
+        "print(\"Decoder start token ID:\", processor.decode([model.config.decoder_start_token_id]))"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "ygTIylugfasG"
+      },
+      "source": [
+        "## Create PyTorch DataLoaders\n",
+        "\n",
+        "Next, we create corresponding PyTorch DataLoaders, which allow us to loop over the dataset in batches:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "metadata": {
+        "id": "nLQ_Vl5MLugu"
+      },
+      "outputs": [],
+      "source": [
+        "from torch.utils.data import DataLoader\n",
+        "\n",
+        "# feel free to increase the batch size if you have a lot of memory\n",
+        "# I'm fine-tuning on Colab and given the large image size, batch size > 1 is not feasible\n",
+        "train_dataloader = DataLoader(train_dataset, batch_size=1, shuffle=True, num_workers=4)\n",
+        "val_dataloader = DataLoader(val_dataset, batch_size=1, shuffle=False, num_workers=4)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "AxtTVgNnfdkD"
+      },
+      "source": [
+        "Let's verify a batch:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 21,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "WHurHlLnL8Xm",
+        "outputId": "3489d45e-8761-40dc-d6c9-1b60af7d8edb"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "torch.Size([1, 3, 1280, 960])\n"
+          ]
+        }
+      ],
+      "source": [
+        "batch = next(iter(train_dataloader))\n",
+        "pixel_values, labels, target_sequences = batch\n",
+        "print(pixel_values.shape)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 22,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "f8ehAwgPZrcc",
+        "outputId": "786ddcaa-4cf7-4613-d3e4-325df6738c7a"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "<s_menu>\n",
+            "<s_nm>\n",
+            "HA\n",
+            "ZE\n",
+            "LN\n",
+            "UT\n",
+            "C\n",
+            "HO\n",
+            "CO\n",
+            "III\n",
+            "(\n",
+            "R\n",
+            ")\n",
+            "</s_nm>\n",
+            "<s_cnt>\n",
+            "1\n",
+            "x\n",
+            "</s_cnt>\n",
+            "<s_discountprice>\n",
+            "1\n",
+            ",\n",
+            "500\n",
+            "</s_discountprice>\n",
+            "<s_price>\n",
+            "2\n",
+            "4,000\n",
+            "</s_price>\n",
+            "</s_menu>\n",
+            "<s_sub_total>\n",
+            "<s_subtotal_price>\n"
+          ]
+        }
+      ],
+      "source": [
+        "for id in labels.squeeze().tolist()[:30]:\n",
+        "  if id != -100:\n",
+        "    print(processor.decode([id]))\n",
+        "  else:\n",
+        "    print(id)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 23,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "IoXL0MnTzmdZ",
+        "outputId": "e9500613-d241-420f-feac-e94ac78ee387"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "800\n",
+            "100\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(len(train_dataset))\n",
+        "print(len(val_dataset))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 24,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "SYdUWe1YzDE8",
+        "outputId": "c38fc7bd-8287-4008-fb69-a8159fa13c9f"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "torch.Size([1, 3, 1280, 960])\n"
+          ]
+        }
+      ],
+      "source": [
+        "# let's check the first validation batch\n",
+        "batch = next(iter(val_dataloader))\n",
+        "pixel_values, labels, target_sequences = batch\n",
+        "print(pixel_values.shape)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 25,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "xbCw5mYH0Mvu",
+        "outputId": "d321a64e-a911-446f-ea2e-a3ce221133de"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "<s_menu><s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>PIZZA TOAST</s_nm><s_cnt>1</s_cnt><s_price>16,000</s_price></s_menu><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>4,500</s_changeprice></s_total></s>\n"
+          ]
+        }
+      ],
+      "source": [
+        "print(target_sequences[0])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "mnmD7rRy2WLI"
+      },
+      "source": [
+        "## Define LightningModule\n",
+        "\n",
+        "Next, we define a [LightningModule](https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_module.html), which is the standard way to train a model in PyTorch Lightning. A LightningModule is an `nn.Module` with some additional functionality. \n",
+        "\n",
+        "Basically, PyTorch Lightning will take care of all device placements (`.to(device)`) for us, as well as the backward pass, putting the model in training mode, etc."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 26,
+      "metadata": {
+        "id": "oRm5i4gWG-sb"
+      },
+      "outputs": [],
+      "source": [
+        "import re\n",
+        "from nltk import edit_distance\n",
+        "import numpy as np\n",
+        "\n",
+        "import pytorch_lightning as pl\n",
+        "\n",
+        "\n",
+        "class DonutModelPLModule(pl.LightningModule):\n",
+        "    def __init__(self, config, processor, model):\n",
+        "        super().__init__()\n",
+        "        self.config = config\n",
+        "        self.processor = processor\n",
+        "        self.model = model\n",
+        "\n",
+        "    def training_step(self, batch, batch_idx):\n",
+        "        pixel_values, labels, _ = batch\n",
+        "        \n",
+        "        outputs = self.model(pixel_values, labels=labels)\n",
+        "        loss = outputs.loss\n",
+        "        self.log(\"train_loss\", loss)\n",
+        "        return loss\n",
+        "\n",
+        "    def validation_step(self, batch, batch_idx, dataset_idx=0):\n",
+        "        pixel_values, labels, answers = batch\n",
+        "        batch_size = pixel_values.shape[0]\n",
+        "        # we feed the prompt to the model\n",
+        "        decoder_input_ids = torch.full((batch_size, 1), self.model.config.decoder_start_token_id, device=self.device)\n",
+        "        \n",
+        "        outputs = self.model.generate(pixel_values,\n",
+        "                                   decoder_input_ids=decoder_input_ids,\n",
+        "                                   max_length=max_length,\n",
+        "                                   early_stopping=True,\n",
+        "                                   pad_token_id=self.processor.tokenizer.pad_token_id,\n",
+        "                                   eos_token_id=self.processor.tokenizer.eos_token_id,\n",
+        "                                   use_cache=True,\n",
+        "                                   num_beams=1,\n",
+        "                                   bad_words_ids=[[self.processor.tokenizer.unk_token_id]],\n",
+        "                                   return_dict_in_generate=True,)\n",
+        "    \n",
+        "        predictions = []\n",
+        "        for seq in self.processor.tokenizer.batch_decode(outputs.sequences):\n",
+        "            seq = seq.replace(self.processor.tokenizer.eos_token, \"\").replace(self.processor.tokenizer.pad_token, \"\")\n",
+        "            seq = re.sub(r\"<.*?>\", \"\", seq, count=1).strip()  # remove first task start token\n",
+        "            predictions.append(seq)\n",
+        "\n",
+        "        scores = []\n",
+        "        for pred, answer in zip(predictions, answers):\n",
+        "            pred = re.sub(r\"(?:(?<=>) | (?=</s_))\", \"\", pred)\n",
+        "            # NOT NEEDED ANYMORE\n",
+        "            # answer = re.sub(r\"<.*?>\", \"\", answer, count=1)\n",
+        "            answer = answer.replace(self.processor.tokenizer.eos_token, \"\")\n",
+        "            scores.append(edit_distance(pred, answer) / max(len(pred), len(answer)))\n",
+        "\n",
+        "            if self.config.get(\"verbose\", False) and len(scores) == 1:\n",
+        "                print(f\"Prediction: {pred}\")\n",
+        "                print(f\"    Answer: {answer}\")\n",
+        "                print(f\" Normed ED: {scores[0]}\")\n",
+        "\n",
+        "        self.log(\"val_edit_distance\", np.mean(scores))\n",
+        "        \n",
+        "        return scores\n",
+        "\n",
+        "    def configure_optimizers(self):\n",
+        "        # you could also add a learning rate scheduler if you want\n",
+        "        optimizer = torch.optim.Adam(self.parameters(), lr=self.config.get(\"lr\"))\n",
+        "    \n",
+        "        return optimizer\n",
+        "\n",
+        "    def train_dataloader(self):\n",
+        "        return train_dataloader\n",
+        "\n",
+        "    def val_dataloader(self):\n",
+        "        return val_dataloader"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "0ZoPiDOPKg0o"
+      },
+      "source": [
+        "## Train!\n",
+        "\n",
+        "Next, let's train! This happens instantiating a PyTorch Lightning `Trainer`, and then calling `trainer.fit`.\n",
+        "\n",
+        "What's great is that we can automatically train on the hardware we have (in our case, a single GPU), enable mixed precision (`fp16=True`, which makes sure we don't consume as much memory), add Weights and Biases logging, and so on. "
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 27,
+      "metadata": {
+        "id": "pxNJhCGjKhtR"
+      },
+      "outputs": [],
+      "source": [
+        "config = {\"max_epochs\":30,\n",
+        "          \"val_check_interval\":0.2, # how many times we want to validate during an epoch\n",
+        "          \"check_val_every_n_epoch\":1,\n",
+        "          \"gradient_clip_val\":1.0,\n",
+        "          \"num_training_samples_per_epoch\": 800,\n",
+        "          \"lr\":3e-5,\n",
+        "          \"train_batch_sizes\": [8],\n",
+        "          \"val_batch_sizes\": [1],\n",
+        "          # \"seed\":2022,\n",
+        "          \"num_nodes\": 1,\n",
+        "          \"warmup_steps\": 300, # 800/8*30/10, 10%\n",
+        "          \"result_path\": \"./result\",\n",
+        "          \"verbose\": True,\n",
+        "          }\n",
+        "\n",
+        "model_module = DonutModelPLModule(config, processor, model)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "6l4byTwPRBZx"
+      },
+      "source": [
+        "We'll use a custom callback to push our model to the hub during training (after each epoch + end of training). For that we'll log into our HuggingFace account."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 28,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000,
+          "referenced_widgets": [
+            "d135d783486d456494d15ef2a339ebff",
+            "74478f6d2baf47999e56952b01ba938f",
+            "24e315cb82a747d6b9566b461db6aee9",
+            "0d2f68be02e7495fab83926f99b93586",
+            "65277dbddbb34381b788a0ee526a0245",
+            "fe0bc6d3aa0b4d88a63aa611af3bf65d",
+            "73094daa6d4c4bbf93bd29b8c0253e09",
+            "f98e3325c6b64df7b028a71eb6c1aa5e",
+            "c5f481bd341a48668518912efbd6a35a",
+            "bfc5138baadf4385a0ed6b87107fabec",
+            "b760aaf9ca3047378404f446549355ef",
+            "5536aeeebaad4d158a11a706940a0220",
+            "3427bc46e6f84ac5a403b42afcde9b08",
+            "b294221a318349228f631ca89407740b",
+            "45df3e9080c7437680d57cb5936dc1de",
+            "4a86c267cbe34ba3bbe0ec2e0035bbbb",
+            "3bcce8d28d894837824f52bae420976a",
+            "ae1f8706e72943989d91f9a44a40eeeb",
+            "bc7bb44709434398a99c395a01d2b3b6",
+            "0e2de7dbc3f3450bb17060ce2687c3ed",
+            "44a17877ab654e0481b0fe827a991e5a",
+            "083ca4f1dea5421bb07bf9cfc802871d",
+            "8249f31d416e4ed388233cd633c212a7",
+            "de3f7930ae454905be655bf33f045280",
+            "5628c489cf31430c8b7efe8118c64815",
+            "b04b0c322c624afa8bb5a128b2af08b6",
+            "b71da8215fd74394aeef7b2835ebdce2",
+            "aad2e43eeafa4cccb5e476d3fce4dacb",
+            "18db9e56c0354600851d762c8de0f774",
+            "a524d30afbdc4574be77a664888d32e6",
+            "30f78b0e910549a6a5e79e8a49c4c67d",
+            "b12a725c43db4fa4ad13d82c75738994",
+            "144e18e547844b1789fa6759bad4b1a2",
+            "cdf0d854eba142779798e0ac495c02af",
+            "bfc6976f3a4b4de3bd42aa1dc9ab73e5",
+            "74cbba5d476540188be2501bf934b5cd",
+            "c08394b19b98474798fc290bc540ddd5",
+            "6fcd1c300caa489dadeaa50c6c814a14",
+            "f60b9e69e69e40189644c2cde41fae18",
+            "297ba8af5a704c5ca34d0f406de3e918",
+            "95ec17f083be45d1a48d643e62f4dbf8",
+            "8a3af3818f69463f845e95c933ac00cd",
+            "b968d28f243543b29cf0733e2d9fc516",
+            "e0f0d44a4e834e9291b2c021fcb1dad9",
+            "e0732c157cbf446f80cd1b4d52f7f6b8",
+            "259d3cba0a5b4943b4b025f921edf06b",
+            "4d6704d874404c9996e32b16b7773169",
+            "0c44b50f550a42d5a89d35c0233fa0bb",
+            "bf3538bb8a33408088307bb3dba05a14",
+            "24c7acb091ab4037a6b4a2eb8a1085e3",
+            "fad67a0d8f834d6eb9609fc0ecec94c8",
+            "9c081ba4b4b7409caef98b8c7754c9b6",
+            "a535138c7cfc454e8a096f31b4625331",
+            "745bf50f671a44bc9abddcc6efb736ee",
+            "07b75ae72a6a4d16a3ff73a1debe2ee5",
+            "082d0b472b90409f8ab9b02391df63a4",
+            "1c2bd9e72e334917b3ce39810bf5ea0b",
+            "2aa84a0d65254ef49ee100f66e393ae9",
+            "87a1b92e248549a5b9b9833d52e85c76",
+            "1cda98448c074471ae879ab9410e49d5",
+            "9a7cb4d7e9514575a93e2f86fc32fb4b",
+            "1c7a17fb7dd041c2949e5df85ee78570",
+            "c6e7bfb4e3144b16bcfd3fd12673d853",
+            "1eecabada33e46da975375f9fce5517e",
+            "1674e26429bc4c80991bb8942b56a7d7",
+            "72e608fe672b40c99de89ad5ce1e33c0",
+            "a35f8906c1ae46828120319694065815",
+            "6340e0aa27c04db0b48448513e9875c4",
+            "c97025e7d015445fafa406c4c1a89af7",
+            "1dc7760bdd2944ad9c4991c82dc86e25",
+            "144c2d74865e41c19a4a6efb4b120ca9",
+            "e8dba2b5fdc94b5598e6ab9f75671cbb",
+            "1c1855ade6204625bfaab54ca2159af5",
+            "210766df14774c1e89d0df73f294daa6",
+            "7171afc8b8dd4e64966065b7f39f2dd6",
+            "6fe01f5548f947d2aebc95273a592581",
+            "c2f3547e877a4f2dac7a1130e6f9acab",
+            "67b22ef1c41541dd99fc2b8d445513d2",
+            "9bbc7693c651492f843088817a65497f",
+            "20eb3303eb2b429891247566f52218c0",
+            "25721e39542d43029d26ac34b4af6d89",
+            "aef15ac1c7214177b7a890917b2a350d",
+            "75e8cbe174904f91b3a9ee3f4572625b",
+            "484fac29339449d58309c92dbbbd2af2",
+            "d216a5de8270482b90d297cf31a09d35",
+            "fc4c72e25d9a4b648c14d03560bba0a2",
+            "58a4b18d859e4c47bc97f2e6ce8c6c73",
+            "6a63b2bbe3f34bc6b9a4258a04ca9104",
+            "9812cfa5ccd14b7aa756a383c793c2c5",
+            "4a2f2fa2885347aebb436467a49b8857",
+            "a7fb70b9171c4958bc5f5c37e51f8cd6",
+            "31d5cb042096428fa4e8a0cd682ddc09",
+            "9f546de07edf4386ae8ef9394eb6c692",
+            "3350308cf34f4c02bd89f6e2a345ed12",
+            "7ec029d2493f40649921347adbb03ae7",
+            "c922e749c8464d2f9080b3bd2333d04f",
+            "1646a7c133a94af7bcfda5fb6ca800bc",
+            "80cc4498465e4fecba040320c9bf1af6",
+            "55e69f30eb7f44dfb9fa64f938cd41dd",
+            "ea7c0bd905074e5d8105bb82036bea1c",
+            "e529a78e1aba43d980b2953aef3cdfba",
+            "25296141a79c4477aac6635dd30a80e5",
+            "2ee2d4a8635f45dba573b749244f9e2a",
+            "404fed29990348b7ac2fba4a5b61aa89",
+            "9b045fecb5c24541b6611ba71237f6f7",
+            "3528f8245a2044c4b2037481bdaf39a7",
+            "047bdaa0ff9d4a4f8d6f46fca23bd0d2",
+            "91f16cb20b2d4590ab22a4b964290569",
+            "82e30cf225894092a6be203ae026b742",
+            "4a987dc4a0e54e5da442be8d6a1c7f09",
+            "cd21d646227b4d478abb70ba04588215",
+            "01b01e7329334686ba39c11ec18e9df5",
+            "2e8a6bd2ef104b32868443ac711c88b6",
+            "0e590d1bb05d4bfaa6c0c41cb41e4794",
+            "279ce49322904b87b2ec18b4f497465c",
+            "15799ffca3624428926e2ddb16728b68",
+            "ac96d471b96049c4aace63a7d88ec166",
+            "86a4453fe0d7495aafe95e8f68f7a44c",
+            "fcb2db503d9a49c3b45282bebec92322",
+            "1384b04401ee4d5e9a7ab9574e660ee6",
+            "86b758931e9b4f6c81b2b5d61bb0ed86",
+            "ca8a046ed39e45f79234a10f85ed09d4",
+            "9d0bb9e6cae5452a8f7909340d0ab21c",
+            "9db7c2d529ea46d48e22271d8432f137",
+            "6d6241a0e8544b03bd406739bd2e3914",
+            "3475f0d8415b4f3ba6b5ad701c365e61",
+            "bb1ee26e35f04a429d3df1f7273b4603",
+            "5b72a50beccd472399740c67d5b8a775",
+            "488139fa453f40e6895a0bac7d5cf840",
+            "d6e90d985e8b4f7fa5d8258c72a8ba9e",
+            "5053663ab6874c378d764dc8584b6aca",
+            "873c26ebd5a0403885933700f87ae39f",
+            "4058a3b2505f441f84f78fe4f7188aa8",
+            "d525b6ed32414b8583d8726d83dd747b",
+            "932854c5974142b3b906ac1db17725fc",
+            "baad5e47bfc940229c7c19cb8372b59c",
+            "3ca24d66c54b42868c814abb11d4214e",
+            "0fe66bd8c6314fdb86ea236d9638f538",
+            "10e6ba61808f471d82b431c607b65d99",
+            "5c9eb0211674488bbe8ec74c68a6e9a3",
+            "f71dd43430aa4d4cb5168644a972df59",
+            "92f74f940eb74ceb89139e25dc1fe869",
+            "b6168e1cb7354844a2ac17dee7a31168",
+            "324b10e8d5ea4f1598111ce9321f5809",
+            "b3d5b8a11f8948d0bb7273e036841869",
+            "caf81cab2e1c45c38007dc88bc9a9e0e",
+            "b30a4626320c4e78b3a033cf257946fe",
+            "d22010093bc54928b96389c8cc48d409",
+            "148b60b8a9a44244874d2db13de48a00",
+            "311acaa0e5844400b54281fe18b50b34",
+            "6016947c02af4021851e950c72479029",
+            "3a6dce72d0ed40c48bbd91b3f07aa67a",
+            "36777dc617bf4589a8ab9802f363ecf4",
+            "f2e58d8539584eebae048ed68d50a641",
+            "9dde5575c8e7438fa2d86e4b9a4fb33f",
+            "18e8af9f9ff247c88797e03d48b675f9",
+            "8cef8071dc984acc8a003134e8d64a11",
+            "cd80b89157374e759c3a24091fced46b",
+            "3563de5d5e394c578b7667bdae8644e6",
+            "2040593b2df341c68670f38512b423d0",
+            "16ea181fc8694d29b499b46678fbdaf3",
+            "e6b5096cac864d27ad88010c2180db29",
+            "e32e4cee40f14064b9cd93b7688c3ff5",
+            "e82ab023dc0e4a2dbe8da18f1b346ca0",
+            "542c34c7d55c400a8f623232403fe250",
+            "0759cda7bd084b02921689bc5e319ba5",
+            "543c3f05eb0547298950b7e7d8c64467",
+            "f414756091e34756a98d812bcf299f69",
+            "d510866a711a4f5bb98748690dc89fbe",
+            "56959726851f49a9b05b1b92cfdd6e74",
+            "3f10740717d4479ba2acf18f7957fc44",
+            "31081f8d85954a33bcc789b1f5f93c56",
+            "ec2fc9e744d9460f9063f9c0aac4c3d5",
+            "8206f8f3de1a4907ae54d474d422633f",
+            "3880476d3f0e4962be29180763486deb",
+            "ce88d1d6c0494245b812ae65ea2654ad",
+            "18f20450f84d48d7839bb3c676cb53d4",
+            "4619abf6125240f7862c7583a6f68af1",
+            "f24b9f61a1fe4c3f86e5086676a5e5d5",
+            "8299c1ef69414603a1604699c777e1f4",
+            "648f377c77da4818b1817ab95677d5bc",
+            "ccd7cb252ac34be1afa95313cd576555",
+            "75469c205b314779aef9d1e7ff2fd612",
+            "2dd3e0f914f6471587bbe40beeacd7f3",
+            "e6f8227c5e914a279428bfc620591ef0",
+            "79c3843d7f6045799cfc76b2bc4f0837",
+            "33170adc2cbe4b3daa9073cee501d854",
+            "8f6e8799b4e1454ea04bb9c94b70fdb8",
+            "9ea85c5be7104fdbb67f52414ba1a1bd",
+            "81ae284f0d064843be6279936fba8a13",
+            "1e25f97059cf482587bc1dcb055d4f7c",
+            "583a3d03b1f344d6b7424589c4db1634",
+            "56628597cea5425684265b293010eefe",
+            "a999d2c30b9644a7967b7109c3aae629",
+            "08c07275cbbe4fd0822c354d99c303ea",
+            "ee9eb1bc7197470487cf0dea02a3d8f9",
+            "a4ddea7815394732a0125128fcd9e1f2",
+            "3da1fd9a348f4c7bb07889c017cc0c2a",
+            "62bad7effcf24059b293404071b83263",
+            "c5d372a9962c49ada49b96a66c5ecd7e",
+            "c2a0bcc5ca8e42439ef2e153193714be",
+            "dd4114a8f79b4725951e78ab4f31d19b",
+            "0dfe3ae073634ba8a1747bc96b30e2bd",
+            "9dcbe88c6ba446ea9584331776d2748a",
+            "9b6856e1b63c46b78a50bee3336577e7",
+            "9cc8e3acf3d74f9796353f621fb6dfbf",
+            "ab1569f009a54b018f8e1d90a51172ed",
+            "d2d0f66f84874e679594bc856182c6c2",
+            "e5562397a34348be901b498203690a42",
+            "cfdf85f797074bc8af900f5623b63e67",
+            "ee26b20d24b94233b242a490bbb528bd",
+            "b64f8b95e23c4baf87fcec7fb16aedfa",
+            "f9bf6bbc52ea46bc8204f3756f2f981b",
+            "f3cb306bf10b448ab173861f392ad1d7",
+            "52cbbbf6bc6643e9b43d844586ab453e",
+            "a071ed8d726f45b4a07251b60793dc6a",
+            "5f71880b66d1458e923cc893a88f91bf",
+            "3e528e7f8cbf4ca597c63d1789a556a5",
+            "4184d862482d4589806f8d09b5b85737",
+            "c99fc92b5c87414faa6bafd1d91ce9c4",
+            "098aae301ab04e688652dd0c05f8de1c",
+            "aff4e5ac7e384d408fc23ca0a8d3658f",
+            "c0cf700f7872458385250ba075a8edb1",
+            "2e6a63d04fd747a280f813b1335a52b1",
+            "dd41ea80146343bcbee92bed78324879",
+            "04b01b03fcc143fa8633b52ec231f026",
+            "10d449f46d9c4502baaad1606f873c09",
+            "44b4f06f3c0841d2ac960337d18de7a3",
+            "dbe52dd9651f42238a11351f10b22b4a",
+            "3f76ca5381b64731af382a63b890292b",
+            "5af452039cad49ee92c938aaffa25765",
+            "05c1c99b4aff486a9c5eeadf9bd8230a",
+            "167cf75950f6434293f6809a84f998f3",
+            "d3995239fdf54fabb7fb42417dd2d1e2",
+            "32cb9bbc1e4547cfbe4df1e4ca70e254",
+            "3e9927167bb84cac9cf56f350bee5aae",
+            "ff830930e9e04bdaa73f57e4eafe1979",
+            "72254d54d49a4054b49882200eecc49b",
+            "cfa9b34f74b541fc9c54b905cffa05ad",
+            "ea0303a1646b454cb26f023c0d8b7804",
+            "a4dc6daaa87e4a4689ffc623b0a3b259",
+            "24b5e61aecd84402a6261b4b06146559",
+            "db3b31f6234f4c0781e02e27c0a78139",
+            "c1f64aaadd484bb2900aaebadeb305d5",
+            "97e80dbb785548e0ad4b7724e91a27f7",
+            "20e0bf2b09d841d6bc9e1f36ec4079bc",
+            "bf9d9715e7684c4e8ac29cbcabf1c600",
+            "e71b1fe193ba49afb42fe50f96663070",
+            "c0c9ce38c68446ddad343c8abc4aa3a9",
+            "a7f7c95743214d17a1cd103c2add1b3c",
+            "699755e8ae9840f0a87246bd89608f67",
+            "1e6e26bf5f3e4322b0f9ff4352976adb",
+            "b38da01ce29b4009bf824a779d4cafe7",
+            "5f3800af43c84d3596987e49afd4961d",
+            "d34ff744caf646e88cb0606d7a6de704",
+            "5c6c3811d9e04247abd52e0f835b6a5e",
+            "fdf8fb828c1d4ad6b864b9197a0aa486",
+            "bb888b3abe26402897177229c0a6ab01",
+            "009ae1d114cb48d0990e934e19ee961f",
+            "aaa6238192004463834b5ee1b3464cff",
+            "299e59499eda4a1db01880e4fb1d5cd2",
+            "b50f6068222b4b7d9c8a865bd41ce277",
+            "ca44a4c94aea499ea738f536eacf4b9b",
+            "582d8cd7787443f59398e2f79c328b51",
+            "821ebf47157741ae9045004304e1d66d",
+            "8f29c28a5f154fcfb6cb2f382eb1e1b1",
+            "c5f9fb53d093461282bc9ebd4a68ead4",
+            "7ddc094c928a4b87a7d5895dc558b15b",
+            "554913277fc34084990cd041ca766701",
+            "e8f2e16d8a9f4091a2d6438892c731b4",
+            "0ce302531a69423aa36a39e0502f7970",
+            "d80a188b254f4bd1be7b3c18442547ea"
+          ]
+        },
+        "id": "NiK6-vQHKnBy",
+        "outputId": "7b5b64fc-9eae-43e0-8598-7bc5f3608cfe"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/home/niels/python_projects/transformers/env/lib/python3.8/site-packages/lightning_fabric/connector.py:563: `precision=16` is supported for historical reasons but its usage is discouraged. Please set your precision to 16-mixed instead!\n",
+            "Using 16bit Automatic Mixed Precision (AMP)\n",
+            "GPU available: True (cuda), used: True\n",
+            "TPU available: False, using: 0 TPU cores\n",
+            "IPU available: False, using: 0 IPUs\n",
+            "HPU available: False, using: 0 HPUs\n",
+            "You are using a CUDA device ('NVIDIA A100-SXM4-80GB') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision\n",
+            "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2,3,4]\n",
+            "\n",
+            "  | Name  | Type                      | Params\n",
+            "----------------------------------------------------\n",
+            "0 | model | VisionEncoderDecoderModel | 201 M \n",
+            "----------------------------------------------------\n",
+            "201 M     Trainable params\n",
+            "0         Non-trainable params\n",
+            "201 M     Total params\n",
+            "807.633   Total estimated model params size (MB)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Epoch 0:  20%|██        | 160/800 [00:25<01:40,  6.37it/s, v_num=1]"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": []
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/home/niels/python_projects/transformers/src/transformers/generation/configuration_utils.py:543: UserWarning: `num_beams` is set to 1. However, `early_stopping` is set to `True` -- this flag is only used in beam-based generation modes. You should set `num_beams>1` or unset `early_stopping`.\n",
+            "  warnings.warn(\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Prediction: <s_menu><s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>13,000</s_price></s_menu><s_total><s_total_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>4,500</s_total_price><s_cashprice>4,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>PIZZA TOAST</s_nm><s_cnt>1</s_cnt><s_price>16,000</s_price></s_menu><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>4,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.5036231884057971\n"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "/home/niels/python_projects/transformers/env/lib/python3.8/site-packages/pytorch_lightning/utilities/data.py:77: Trying to infer the `batch_size` from an ambiguous collection. The batch size we found is 1. To avoid any miscalculations, use `self.log(..., batch_size=batch_size)`.\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Prediction: <s_menu><s_nm>Kopi Susu Kolonel</s_nm><s_cnt>1</s_cnt><s_price>23.000</s_price></s_menu><s_total><s_total_price>23.000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>27.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Kopi Susu Kolonel</s_nm><s_cnt>1</s_cnt><s_price>23.000</s_price></s_menu><s_total><s_total_price>23.000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>27.000</s_changeprice></s_total>\n",
+            " Normed ED: 0.0\n",
+            "Prediction: <s_menu><s_nm>S-Ovaltine</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_unitprice><s_cnt>18,181</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_cashprice><s_changeprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>S-Ovaltine 50%</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price><s_vatyn>10% Tax Included</s_vatyn></s_menu><s_sub_total><s_subtotal_price>18,181</s_subtotal_price><s_tax_price>1,818</s_tax_price></s_sub_total><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.32460732984293195\n",
+            "Prediction: <s_menu><s_nm>M-Caramel Black Tea</s_nm><s_cnt>1</s_cnt><s_price>28,000</s_unitprice><s_cnt>1X</s_cnt><s_price>28,000</s_unitprice><s_cnt>1X</s_cnt><s_price>28,000</s_subtotal_price></s_sub_total><s_total><s_total_price>28,000</s_total_price><s_cashprice>28,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>M-Caramel Black Tea</s_nm><s_unitprice>@28,000</s_unitprice><s_cnt>1X</s_cnt><s_price>28,000</s_price><s_sub><s_nm>70%</s_nm><sep/><s_nm>Less Ice</s_nm></s_sub></s_menu><s_sub_total><s_subtotal_price>28,000</s_subtotal_price><s_tax_price>0</s_tax_price></s_sub_total><s_total><s_total_price>28,000</s_total_price><s_cashprice>28,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.3009950248756219\n",
+            "Prediction: <s_menu><s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price></s_menu><s_total><s_total_price>41,000</s_total_price><s_cashprice>- Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>41,000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>9000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><s_sub><s_nm>Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>41,000</s_subtotal_price></s_sub_total><s_total><s_total_price>41,000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>:9,000</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.3447368421052632\n",
+            "Prediction: <s_menu><s_nm>LE MINERAL</s_nm><s_cnt>1</s_cnt><s_price>8,000</s_price></s_menu><s_sub_total><s_subtotal_price>727</s_subtotal_price></s_sub_total><s_total><s_total_price>727</s_total_price><s_cashprice>8,000</s_cashprice><s_changeprice>8,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>LE MINERAL</s_nm><s_cnt>1.00</s_cnt><s_price>8,000</s_price></s_menu><s_sub_total><s_subtotal_price>7,273</s_subtotal_price><s_tax_price>727</s_tax_price></s_sub_total><s_total><s_total_price>8,000</s_total_price><s_cashprice>8,000</s_cashprice></s_total>\n",
+            " Normed ED: 0.22304832713754646\n",
+            "Prediction: <s_menu><s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>52,000</s_price></s_menu><s_sub_total><s_subtotal_price>123,000</s_total_price><s_cashprice>123,000</s_total_price><s_cashprice>123,000</s_cashprice><s_changeprice>\n",
+            "    Answer: <s_menu><s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>OREO GREEN TEA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price><sep/><s_nm>WHITE CHOCO BANANA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price></s_menu><s_total><s_total_price>123,000</s_total_price><s_creditcardprice>123,000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.39893617021276595\n",
+            "Prediction: <s_menu><s_nm>Choco Devil</s_nm><s_cnt>4</s_cnt><s_price>63.636</s_price></s_menu><s_sub_total><s_subtotal_price>63.636</s_price></s_menu><s_sub_total><s_subtotal_price>-9,545</s_price></s_menu><s_sub_total><s_subtotal_price>-9,545</s_tax_price></s_sub_total><s_total><s_total_price>5,409</s_tax_price></s_sub_total><s_total><s_total_price>59,500</s_total_price><s_cashprice>100,500</s_total_price><s_cashprice>40,500</s_cashprice><s_changeprice>:</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>Choco Devil</s_nm><s_cnt>4</s_cnt><s_discountprice>-9,545</s_discountprice><s_price>63,636</s_price></s_menu><s_sub_total><s_subtotal_price>63,636</s_subtotal_price><s_discount_price>-9,545</s_discount_price><s_tax_price>5,409</s_tax_price></s_sub_total><s_total><s_total_price>59,500</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>40,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.321353065539112\n",
+            "Prediction: <s_menu><s_nm>TALAM UNGU</s_nm><s_cnt>3X</s_cnt><s_price>19,500</s_price></s_menu><s_sub_total><s_subtotal_price>TALAM UNGU</s_nm><s_cnt>1</s_cnt><s_price>19,500</s_price></s_menu><s_sub_total><s_subtotal_price>-40.000%</s_price></s_menu><s_sub_total><s_subtotal_price>-7,800</s_price></s_menu><s_sub_total><s_subtotal_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>4.00xITEMs</s_nm><s_cnt>11,700</s_total_price><s_cashprice>11,700</s_cashprice><s_changeprice>8,300</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>TALAM UNGU</s_nm><s_unitprice>@6500</s_unitprice><s_cnt>3X</s_cnt><s_discountprice>-7,800</s_discountprice><s_price>19,500</s_price><sep/><s_nm>MIKA KECIL</s_nm><s_unitprice>@0</s_unitprice><s_cnt>1X</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>11,700</s_subtotal_price></s_sub_total><s_total><s_total_price>11,700</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>8,300</s_changeprice><s_menuqty_cnt>4.00xITEMs</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.46107784431137727\n",
+            "Prediction: <s_menu><s_nm>Tahu Ikan Oma Gisk</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price></s_menu><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Tahu Ikan Oma Giok</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.01904761904761905\n",
+            "Prediction: <s_menu><s_nm>Serbu</s_nm><s_cnt>1</s_cnt><s_price>40.000</s_price></s_menu><s_sub_total><s_subtotal_price>2</s_cnt><s_price>20.000</s_price></s_menu><s_total><s_total_price>60.000</s_total_price><s_cashprice>60.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Serbu 1</s_nm><s_cnt>2</s_cnt><s_price>40.000</s_price><sep/><s_nm>Choco Peanut Bread</s_nm><s_cnt>2</s_cnt><s_price>20.000</s_price></s_menu><s_total><s_total_price>60.000</s_total_price><s_cashprice>60.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.1371841155234657\n",
+            "Prediction: <s_menu><s_nm>Se'I Sapi Sambal Matah ( R )</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price></s_menu><s_sub_total><s_subtotal_price>20.000</s_price></s_menu><s_sub_total><s_subtotal_price>35.000</s_total_price><s_cashprice>10.000</s_cashprice><s_changeprice>2</s_cnt><s_price>10.000</s_cashprice><s_changeprice>16.000</s_total_price><s_cashprice>100</s_total_price><s_cashprice>100</s_total_price><s_cashprice>100</s_total_price><s_cashprice>100</s_total_price><s_cashprice>100</s_total_price><s_cashprice>89.100</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Se'I Sapi Sambal Matah ( R )</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price><sep/><s_nm>Se'I Sapi Lada Hitam (J)</s_nm><s_cnt>1</s_cnt><s_price>35.000</s_price><sep/><s_nm>Nasi Putih</s_nm><s_cnt>2</s_cnt><s_price>10.000</s_price><sep/><s_nm>Milk Shake Coklat</s_nm><s_cnt>1</s_cnt><s_price>16.000</s_price></s_menu><s_sub_total><s_subtotal_price>81.000</s_subtotal_price><s_tax_price>8.100</s_tax_price></s_sub_total><s_total><s_total_price>89.100</s_total_price><s_changeprice>0</s_changeprice><s_creditcardprice>89.100</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.4283185840707965\n",
+            "Prediction: <s_menu><s_nm>ES KOPI SUSU</s_nm><s_cnt>4</s_cnt><s_price>72.000</s_price></s_menu><s_total><s_total_price>72.000</s_total_price><s_cashprice>72.000</s_total_price><s_cashprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>ES KOPI SUSU</s_nm><s_cnt>4</s_cnt><s_price>72.000</s_price></s_menu><s_total><s_total_price>72.000</s_total_price><s_changeprice>0</s_changeprice><s_emoneyprice>72.000</s_emoneyprice></s_total>\n",
+            " Normed ED: 0.14903846153846154\n",
+            "Prediction: <s_menu><s_nm>MINERAL 600 ML</s_nm><s_cnt>1</s_cnt><s_price>7,727</s_price></s_menu><s_sub_total><s_subtotal_price>7,727</s_price></s_menu><s_sub_total><s_subtotal_price>33,636</s_price></s_menu><s_sub_total><s_subtotal_price>41,364</s_subtotal_price></s_sub_total><s_total><s_total_price>4,136</s_total_price><s_cashprice>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>-4,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>MINERAL 600 ML</s_nm><s_cnt>1</s_cnt><s_price>7,727</s_price><sep/><s_nm>BULGOGI RICE R</s_nm><s_cnt>1</s_cnt><s_price>33,636</s_price></s_menu><s_sub_total><s_subtotal_price>41,364</s_subtotal_price><s_tax_price>4,136</s_tax_price></s_sub_total><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>-4,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.25176470588235295\n",
+            "Prediction: <s_menu><s_nm>Arem Arem Arem Arem Arem Arem Arem</s_nm><s_cnt>2x</s_cnt><s_price>24.000</s_unitprice><s_cnt>2x</s_cnt><s_price>24.000</s_unitprice><s_cnt>1x</s_cnt><s_price>12.000</s_unitprice><s_cnt>1x</s_cnt><s_price>12.000</s_unitprice><s_cnt>Rp 36.000</s_total_price><s_cashprice>Rp 39.600</s_total_price><s_cashprice>Rp 39.600</s_total_price><s_cashprice>Rp 39.600</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Arem Arem</s_nm><s_unitprice>@ 12.000</s_unitprice><s_cnt>2 x</s_cnt><s_price>24.000</s_price><sep/><s_nm>Kroket</s_nm><s_unitprice>@ 12.000</s_unitprice><s_cnt>1 x</s_cnt><s_price>12.000</s_price></s_menu><s_sub_total><s_subtotal_price>Rp 36.000</s_subtotal_price><s_tax_price>Rp 3.600</s_tax_price></s_sub_total><s_total><s_total_price>Rp 39.600</s_total_price><s_emoneyprice>Rp 39.600</s_emoneyprice></s_total>\n",
+            " Normed ED: 0.38875878220140514\n",
+            "Prediction: <s_menu><s_nm>Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Arem Aremploy</s_tax_price></s_sub_total><s_total><s_total_price>Rp 54.000</s_total_price><s_cashprice>Rp 59.400</s_total_price><s_cashprice>Rp 100.000</s_cashprice><s_changeprice>Rp 40.600</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Arem Arem</s_nm><s_unitprice>12.000</s_unitprice><s_cnt>2</s_cnt><s_price>24.000</s_price><sep/><s_nm>Pepenero Pastel</s_nm><s_unitprice>15.000</s_unitprice><s_cnt>2</s_cnt><s_price>30.000</s_price></s_menu><s_sub_total><s_subtotal_price>Rp 54.000</s_subtotal_price><s_tax_price>Rp 5.400</s_tax_price></s_sub_total><s_total><s_total_price>Rp 59.400</s_total_price><s_cashprice>Rp 100.000</s_cashprice><s_changeprice>Rp 40.600</s_changeprice></s_total>\n",
+            " Normed ED: 0.5032258064516129\n",
+            "Prediction: <s_menu><s_nm>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>TT</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.0944206008583691\n",
+            "Prediction: <s_menu><s_nm>LEMONADE 16OZ</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_unitprice><s_cnt>1</s_cnt><s_price>20.000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_subtotal_price></s_sub_total><s_total><s_total_price>20.000</s_total_price><s_cashprice>100,000</s_total_price><s_cashprice>80,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>LEMONADE 16OZ</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_subtotal_price></s_sub_total><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80.000</s_changeprice></s_total>\n",
+            " Normed ED: 0.14681440443213298\n",
+            "Prediction: <s_menu><s_nm>beef C roll 3pcs</s_nm><s_cnt>1</s_cnt><s_price>10,000</s_unitprice><s_cnt>1</s_cnt><s_price>10,000</s_price></s_menu><s_total><s_total_price>15,000</s_total_price><s_cashprice>15,000</s_cashprice><s_changeprice>2</s_cnt><s_price>15,000</s_total_price><s_cashprice>25,000</s_cashprice><s_changeprice>75,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>beef C roll 3pcs</s_nm><s_unitprice>10,000</s_unitprice><s_cnt>1</s_cnt><s_price>10,000</s_price><sep/><s_nm>kaya bred</s_nm><s_unitprice>15,000</s_unitprice><s_cnt>1</s_cnt><s_price>15,000</s_price></s_menu><s_total><s_total_price>25,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>75,000</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.31758530183727035\n",
+            "Prediction: <s_menu><s_nm>FUTAMI GREEN TEA (CLAS</s_nm><s_cnt>1</s_cnt><s_price>12,500</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>13,000</s_price></s_menu><s_sub_total><s_subtotal_price>17,000</s_subtotal_price></s_sub_total><s_total><s_total_price>42,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>7,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>FUTAMI 17 GREEN TEA (CLAS</s_nm><s_cnt>1</s_cnt><s_price>12,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>GRAIN CROQUE MONSIEUR</s_nm><s_cnt>1</s_cnt><s_price>17,000</s_price></s_menu><s_total><s_total_price>42,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>7,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.2648648648648649\n",
+            "Prediction: <s_menu><s_nm>JAMUR</s_nm><s_cnt>2</s_cnt><s_price>10,000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>5,000</s_price></s_menu><s_sub_total><s_subtotal_price>15,000</s_subtotal_price></s_sub_total><s_total><s_total_price>1,500</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>3,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>JAMUR</s_nm><s_cnt>2</s_cnt><s_price>10,000</s_price><sep/><s_nm>TAHU</s_nm><s_cnt>1</s_cnt><s_price>5,000</s_price></s_menu><s_sub_total><s_subtotal_price>15,000</s_subtotal_price><s_tax_price>1,500</s_tax_price></s_sub_total><s_total><s_total_price>16,500</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>3,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.16939890710382513\n",
+            "Prediction: <s_menu><s_nm>Mango Lemon Tea</s_nm><s_cnt>1</s_cnt><s_price>Rp29,090</s_price></s_menu><s_sub_total><s_subtotal_price>Rp113,636</s_price></s_menu><s_sub_total><s_subtotal_price>Rp86,363</s_price></s_menu><s_sub_total><s_subtotal_price>Rp34,363</s_subtotal_price></s_sub_total><s_total><s_total_price>Rp9,736</s_total_price><s_cashprice>Rp20,446</s_total_price><s_cashprice>Rp224,908</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>Mango Lemon Tea</s_nm><s_cnt>1</s_cnt><s_price>Rp 29,090</s_price><sep/><s_nm>Sliders Set</s_nm><s_cnt>1</s_cnt><s_price>Rp 113,636</s_price><sep/><s_nm>Chicken Vege Rice Bowl</s_nm><s_cnt>1</s_cnt><s_price>Rp 86,363</s_price><sep/><s_nm>Discount BCA 15%</s_nm><s_cnt>1</s_cnt><s_price>-Rp 34,363</s_price></s_menu><s_sub_total><s_subtotal_price>Rp 194,726</s_subtotal_price><s_service_price>Rp 9,736</s_service_price><s_tax_price>Rp 20,446</s_tax_price></s_sub_total><s_total><s_total_price>Rp 224,908</s_total_price><s_creditcardprice>Rp 224,908</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.4500846023688663\n",
+            "Prediction: <s_menu><s_nm>RedVelvet Nutella</s_nm><s_cnt>1</s_cnt><s_price>280,000</s_price></s_menu><s_sub_total><s_subtotal_price>280,000</s_price></s_menu><s_total><s_total_price>280,000</s_total_price><s_cashprice>28,000</s_cashprice><s_changeprice>308,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>RedVelvet Nutella</s_nm><s_cnt>1</s_cnt><s_price>280,000</s_price><s_sub><s_nm>Free Mini Candle</s_nm><s_cnt>.5</s_cnt><sep/><s_nm>Large Box</s_nm><s_cnt>1</s_cnt></s_sub></s_menu><s_sub_total><s_subtotal_price>280,000</s_subtotal_price><s_tax_price>28,000</s_tax_price></s_sub_total><s_total><s_total_price>308,000</s_total_price><s_creditcardprice>308,000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.4339152119700748\n",
+            "Prediction: <s_menu><s_nm>BUBBLE GUM</s_nm><s_cnt>1</s_cnt><s_price>18,182</s_price></s_menu><s_sub_total><s_subtotal_price>18,18</s_tax_price></s_sub_total><s_total><s_total_price>18</s_tax_price></s_sub_total><s_total><s_total_price>18</s_tax_price></s_sub_total><s_total><s_total_price>18</s_tax_price></s_sub_total><s_total><s_total_price>18</s_tax_price></s_sub_total><s_total><s_total_price>1</s_cnt><s_price>18</s_tax_price></s_sub_total><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>\n",
+            "    Answer: <s_menu><s_nm>BUBBLE GUM</s_nm><s_cnt>1</s_cnt><s_price>18,182</s_price></s_menu><s_sub_total><s_subtotal_price>18,182</s_subtotal_price><s_tax_price>1,818</s_tax_price></s_sub_total><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.5249110320284698\n",
+            "Prediction: <s_menu><s_nm>PAIN AU CHOCOLATE</s_nm><s_cnt>1</s_cnt><s_price>11,000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>9,000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>13,500</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_total_price><s_cashprice>100,500</s_cashprice><s_changeprice>19,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>PAIN AU CHOCOLATE</s_nm><s_cnt>1</s_cnt><s_price>11,000</s_price><sep/><s_nm>CHOCO CUSTARD PASTRY</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>MILK PASTRY ROLL</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>REAL CHEESE INSIDE BREAD</s_nm><s_cnt>1</s_cnt><s_price>13,500</s_price><sep/><s_nm>SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>15,000</s_price><sep/><s_nm>HAM CHEESE FLAT BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>80,500</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>19,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.3848684210526316\n",
+            "Prediction: <s_menu><s_nm>Prs Sop Sui Jiao</s_nm><s_cnt>1Prs Ha Kaou Udng</s_nm><s_cnt>1Prs Sio May Kpting</s_nm><s_cnt>1Prs Siomay</s_nm><s_cnt>1Prs Siomay</s_nm><s_cnt>1Prs Licp Sniったり<s_nm>1Prs Mio</s_nm><s_cnt>1Prs Mio</s_nm><s_cnt>1Prs Mio</s_nm><s_cnt>1Prs Siomay</s_nm><s_cnt>1Prs Mio</s_nm><s_cnt>1Prs Mio</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_tax_price></s_sub_total><s_total><s_total_price>7,000</s_total_price><s_cashprice>180,000</s_total_price><s_cashprice>18,900</s_total_price><s_cashprice>207,900</s_total_price><s_cashprice>7</s_changeprice><s_menuqty_cnt>7</s_changeprice><s_menuqty_cnt>7</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Sop Sui Jiao</s_nm><s_cnt>1Prs</s_cnt><s_price>33,000</s_price><sep/><s_nm>Ha Kaou Udng</s_nm><s_cnt>1Prs</s_cnt><s_price>28,000</s_price><sep/><s_nm>Sio May Kpting</s_nm><s_cnt>1Prs</s_cnt><s_price>23,500</s_price><sep/><s_nm>Siomay Kmbinasi</s_nm><s_cnt>1Prs</s_cnt><s_price>23,000</s_price><sep/><s_nm>Leng Hong Kien</s_nm><s_cnt>1Prs</s_cnt><s_price>30,000</s_price><sep/><s_nm>Mie Trsi Kgkung</s_nm><s_cnt>1Prs</s_cnt><s_price>35,500</s_price><sep/><s_nm>Es Teh Tawar</s_nm><s_cnt>1Gls</s_cnt><s_price>7,000</s_price></s_menu><s_sub_total><s_subtotal_price>180,000</s_subtotal_price><s_service_price>9,000</s_service_price><s_tax_price>18,900</s_tax_price></s_sub_total><s_total><s_total_price>207,900</s_total_price><s_menutype_cnt>7</s_menutype_cnt><s_menuqty_cnt>7</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.4827586206896552\n",
+            "Prediction: <s_menu><s_nm>NASI MERAH/PUTIH</s_nm><s_cnt>1x5,000</s_unitprice><s_cnt>1x</s_cnt><s_price>5,000</s_price></s_menu><s_sub_total><s_subtotal_price>5,000</s_unitprice><s_cnt>1x6.000</s_unitprice><s_cnt>2x6</s_tax_price></s_sub_total><s_total><s_total_price>8,000</s_total_price><s_cashprice>2.000</s_total_price><s_cashprice>2.000</s_cashprice><s_changeprice>1x14.000</s_cashprice><s_changeprice>1x6.000</s_changeprice><s_menuqty_cnt>1x6.000</s_changeprice><s_menuqty_cnt>1x6.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>NASI MERAH/PUTIH</s_nm><s_unitprice>5.000</s_unitprice><s_cnt>1x</s_cnt><s_price>5.000</s_price><sep/><s_nm>SAYUR</s_nm><s_unitprice>4.000</s_unitprice><s_cnt>2x</s_cnt><s_price>8.000</s_price><sep/><s_nm>KERUPUK/SAMBEL</s_nm><s_unitprice>2.000</s_unitprice><s_cnt>1x</s_cnt><s_price>2.000</s_price><sep/><s_nm>AYAM</s_nm><s_unitprice>14.000</s_unitprice><s_cnt>1x</s_cnt><s_price>14.000</s_price><sep/><s_nm>MINUMAN KEMASAN/REFILL</s_nm><s_unitprice>6.000</s_unitprice><s_cnt>1x</s_cnt><s_price>6.000</s_price></s_menu><s_total><s_total_price>Rp. 35.000</s_total_price></s_total>\n",
+            " Normed ED: 0.47474747474747475\n",
+            "Prediction: <s_menu><s_nm>THAI ICED TEA (L)</s_nm><s_cnt>1</s_cnt><s_price>16,363</s_price></s_menu><s_sub_total><s_subtotal_price>16,36</s_subtotal_price></s_sub_total><s_total><s_total_price>1</s_cnt><s_price>16,999</s_total_price><s_cashprice>16,999</s_total_price><s_cashprice>16,9</s_tax_price></s_sub_total><s_total><s_total_price>17,999</s_total_price><s_cashprice>16,9</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>THAI ICED TEA (L)</s_nm><s_unitprice>16,363</s_unitprice><s_cnt>1</s_cnt><s_price>16.363</s_price></s_menu><s_sub_total><s_subtotal_price>16,363</s_subtotal_price><s_tax_price>1,636</s_tax_price></s_sub_total><s_total><s_total_price>17,999</s_total_price><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.3487179487179487\n",
+            "Prediction: <s_menu><s_nm>ELEPHANT READ BEAN</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>12,000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>1</s_cnt><s_price>10,000</s_unitprice><s_cnt>1</s_cnt><s_price>10,000</s_unitprice><s_cnt>1</s_cnt><s_price>10,000</s_cashprice><s_changeprice>22,000</s_total_price><s_cashprice>22,000</s_total_price><s_cashprice>22,000</s_total_price><s_cashprice>22,000</s_total_price><s_cashprice>22,000</s_total_price><s_cashprice>22,000</s_total_price><s_cashprice>2</s_cnt><s_price>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>ELEPHANT READ BEAN</s_nm><s_unitprice>12,000</s_unitprice><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>chapsal twister donnut</s_nm><s_unitprice>10,000</s_unitprice><s_cnt>1</s_cnt><s_price>10,000</s_price></s_menu><s_total><s_total_price>22,000</s_total_price><s_cashprice>22,000</s_cashprice><s_changeprice>0</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.46557377049180326\n",
+            "Prediction: <s_menu><s_nm>Sabun Beras</s_nm><s_cnt>1</s_cnt><s_price>30000</s_price></s_menu><s_sub_total><s_subtotal_price>30000</s_unitprice><s_cnt>1</s_cnt><s_price>30000</s_subtotal_price></s_sub_total><s_total><s_total_price>3</s_cnt><s_price>3</s_cnt><s_price>3</s_cnt><s_price>3</s_cnt><s_price>50000</s_total_price><s_cashprice>20000</s_total_price><s_cashprice>20000</s_cashprice><s_changeprice>20000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Sabun Beras</s_nm><s_unitprice>30000</s_unitprice><s_cnt>1</s_cnt><s_price>30000</s_price></s_menu><s_sub_total><s_subtotal_price>30000</s_subtotal_price><s_discount_price>Discount(0%)</s_discount_price></s_sub_total><s_total><s_cashprice>50000</s_cashprice><s_changeprice>20000</s_changeprice></s_total>\n",
+            " Normed ED: 0.41371158392434987\n",
+            "Prediction: <s_menu><s_nm>REDBEAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price></s_menu><s_sub_total><s_subtotal_price>12,000</s_price></s_menu><s_total><s_total_price>21,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>29,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>REDBEAN BRE/D</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>FRANKFRUT S/USAGE ROLL</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price></s_menu><s_total><s_total_price>21,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>29,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.16838487972508592\n",
+            "Prediction: <s_menu><s_nm>PREMIUM TOAST PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>24,000</s_price></s_menu><s_total><s_total_price>24,000</s_total_price><s_cashprice>24,000</s_total_price><s_cashprice>24,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>PREMIUM TOAST PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>24,000</s_price></s_menu><s_total><s_total_price>24,000</s_total_price><s_cashprice>24,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.14\n",
+            "Prediction: <s_menu><s_nm>Nasi (MLY)</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price></s_menu><s_total><s_total_price>6.000</s_total_price><s_cashprice>6.000</s_total_price><s_cashprice>6.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Nasi (MLY)</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price></s_menu><s_sub_total><s_subtotal_price>6.000</s_subtotal_price></s_sub_total><s_total><s_total_price>6.000</s_total_price><s_emoneyprice>6.000</s_emoneyprice></s_total>\n",
+            " Normed ED: 0.23333333333333334\n",
+            "Prediction: <s_menu><s_nm>GRAINS PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,500</s_price></s_menu><s_sub_total><s_subtotal_price>20,500</s_price></s_menu><s_sub_total><s_subtotal_price>20,500</s_price></s_menu><s_sub_total><s_subtotal_price>37,000</s_price></s_menu><s_sub_total><s_subtotal_price>57,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>7,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>GRAINS PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,500</s_price><sep/><s_nm>ICED HIBISCUS LYCHEE TEA</s_nm><s_cnt>1</s_cnt><s_price>37,000</s_price></s_menu><s_total><s_total_price>57,500</s_total_price><s_total_etc>50,000</s_total_etc><s_cashprice>7,500</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.3152454780361757\n",
+            "Prediction: <s_menu><s_nm>GRILLED BABY POTATO (R</s_nm><s_cnt>1</s_cnt><s_price>50,500</s_price></s_menu><s_sub_total><s_subtotal_price>76,000</s_price></s_menu><s_sub_total><s_subtotal_price>70,500</s_price></s_menu><s_sub_total><s_subtotal_price>46,000</s_total_price><s_cashprice>243,000</s_total_price><s_cashprice>14,580</s_total_price><s_cashprice>25,758</s_cashprice><s_changeprice>283,338</s_total_price><s_cashprice>283,338</s_total_price><s_cashprice>283,358</s_total_price><s_cashprice>5962</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>GRILLED BABY POTATO (R</s_nm><s_cnt>1</s_cnt><s_price>50,500</s_price><sep/><s_nm>TRUFFLE CREAM</s_nm><s_cnt>1</s_cnt><s_price>76,000</s_price><sep/><s_nm>CARBONARA</s_nm><s_cnt>1</s_cnt><s_price>70,500</s_price><sep/><s_nm>ORIGINAL BREWED TEA</s_nm><s_cnt>2</s_cnt><s_price>46,000</s_price></s_menu><s_sub_total><s_subtotal_price>243,000</s_subtotal_price><s_service_price>14,580</s_service_price><s_tax_price>25,758</s_tax_price></s_sub_total><s_total><s_total_price>283,338</s_total_price><s_creditcardprice>283,338<sep/>5962</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.4353146853146853\n",
+            "Prediction: <s_menu><s_nm>BLACK PERPER MEATBALL</s_nm><s_cnt>1</s_cnt><s_price>76,500</s_price></s_menu><s_sub_total><s_subtotal_price>76,500</s_price></s_menu><s_sub_total><s_subtotal_price>82,000</s_price></s_menu><s_sub_total><s_subtotal_price>56,000</s_price></s_menu><s_sub_total><s_subtotal_price>46,000</s_total_price><s_cashprice>BREWED TEA</s_nm><s_cnt>2</s_cnt><s_price>261,000</s_total_price><s_cashprice>15,660</s_total_price><s_cashprice>27,666</s_total_price><s_cashprice>304,326</s_cashprice><s_changeprice>\n",
+            "    Answer: <s_menu><s_nm>BLACK PEPPER MEATBALL</s_nm><s_cnt>1</s_cnt><s_price>76,500</s_price><sep/><s_nm>QUARTO FORMANGGI PASTA</s_nm><s_cnt>1</s_cnt><s_price>82,500</s_price><sep/><s_nm>GREEN TEA WITH CRUMBLE</s_nm><s_cnt>1</s_cnt><s_price>56,000</s_price><sep/><s_nm>ORIGINAL BREWED TEA</s_nm><s_cnt>2</s_cnt><s_price>46,000</s_price></s_menu><s_sub_total><s_subtotal_price>261,000</s_subtotal_price><s_service_price>15,660</s_service_price><s_tax_price>27,666</s_tax_price></s_sub_total><s_total><s_total_price>304,326</s_total_price></s_total>\n",
+            " Normed ED: 0.4823091247672253\n",
+            "Prediction: <s_menu><s_nm>Soft Ori 3 Top</s_nm><s_cnt>1</s_cnt><s_price>17,272</s_price></s_menu><s_sub_total><s_subtotal_price>17,272</s_tax_price></s_sub_total><s_total><s_total_price>17,27</s_tax_price></s_sub_total><s_total><s_total_price>17,27</s_total_price><s_cashprice>18,999</s_total_price><s_cashprice>18,999</s_total_price><s_cashprice>18,999</s_total_price><s_cashprice>18,999</s_total_price><s_cashprice>18,999</s_total_price><s_cashprice>18,999</s_cashprice><s_changeprice>18,999</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Soft Ori 3 Top</s_nm><s_cnt>1</s_cnt><s_price>17,272</s_price><s_sub><s_nm>Top Oreo</s_nm><s_price>0</s_price><sep/><s_nm>Top Oreo</s_nm><s_price>0</s_price><sep/><s_nm>Top Banana</s_nm><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>17,272</s_subtotal_price><s_tax_price>1,727</s_tax_price></s_sub_total><s_total><s_total_price>18,999</s_total_price><s_cashprice>18,999</s_cashprice></s_total>\n",
+            " Normed ED: 0.4378698224852071\n",
+            "Prediction: <s_menu><s_nm>Ice Lemon Tea</s_nm><s_cnt>1</s_cnt><s_price>13,6</s_price></s_menu><s_sub_total><s_subtotal_price>50,000</s_price></s_menu><s_sub_total><s_subtotal_price>63,636</s_subtotal_price></s_sub_total><s_total><s_total_price>6,364</s_total_price><s_cashprice>70,000</s_total_price><s_cashprice>70,000</s_cashprice><s_changeprice>50,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Ice Lemon Tea</s_nm><s_price>13,636</s_price><sep/><s_nm>-<sep/>Gyro Platter Regular</s_nm><s_price>50,000</s_price></s_menu><s_sub_total><s_subtotal_price>63,636</s_subtotal_price><s_tax_price>6,364</s_tax_price></s_sub_total><s_total><s_total_price>70,000</s_total_price><s_cashprice>70,000</s_cashprice></s_total>\n",
+            " Normed ED: 0.34782608695652173\n",
+            "Prediction: <s_menu><s_nm>TT</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>100,000</s_cashprice><s_changeprice>-80.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>TT</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.2966101694915254\n",
+            "Prediction: <s_menu><s_nm>PKT TEL OR VERKEDEL「</s_nm><s_cnt>26,000</s_price></s_menu><s_sub_total><s_subtotal_price>26,000</s_price></s_menu><s_sub_total><s_subtotal_price>25,000</s_price></s_menu><s_sub_total><s_subtotal_price>25,000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_subtotal_price></s_sub_total><s_total><s_total_price>8,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>2,100</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>PKT TELOR/PERKEDEL</s_nm><s_price>26,000</s_price><sep/><s_nm>TERONG</s_nm><s_price>12,000</s_price><sep/><s_nm>PARU</s_nm><s_price>23,000</s_price><sep/><s_nm>SBL GR ATI/AMPLA</s_nm><s_price>20,000</s_price><sep/><s_nm>NESTLE 330 ML</s_nm><s_price>8,000</s_price></s_menu><s_sub_total><s_subtotal_price>89,000</s_subtotal_price><s_tax_price>8,900</s_tax_price></s_sub_total><s_total><s_total_price>97,900</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>2,100</s_changeprice><s_menuqty_cnt>5.00</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.37636363636363634\n",
+            "Prediction: <s_menu><s_nm>Gojek Chicken</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price></s_menu><s_sub_total><s_subtotal_price>95,000</s_price></s_menu><s_sub_total><s_subtotal_price>95,000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>180,000</s_price></s_menu><s_sub_total><s_subtotal_price>70,000</s_subtotal_price></s_sub_total><s_total><s_total_price>345,000</s_total_price><s_cashprice>34,500</s_total_price><s_cashprice>379,500</s_total_price><s_cashprice>379,500</s_total_price><s_cashprice>379,500</s_total_price><s_cashprice>379,500</s_total_price><s_cashprice>379,500</s_total_price><s_cashprice>379,500</s_total_price><s_cashprice>379,500</s_total_price><s_cashprice>काे පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර පියවර\n",
+            "    Answer: <s_menu><s_nm>Gojek Chicken Chilli Sauce H</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>Gojek Chicken Soy Sauce F</s_nm><s_cnt>1</s_cnt><s_price>180,000</s_price><sep/><s_nm>Gojek French Fries</s_nm><s_cnt>1</s_cnt><s_price>70,000</s_price></s_menu><s_sub_total><s_subtotal_price>345,000</s_subtotal_price><s_discount_price>0</s_discount_price><s_service_price>0</s_service_price><s_tax_price>34,500</s_tax_price></s_sub_total><s_total><s_total_price>379,500</s_total_price></s_total>\n",
+            " Normed ED: 0.9254208395482634\n",
+            "Prediction: 0</s_nm><s_cnt>1</s_cnt><s_price>150,000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>1</s_cnt><s_price>230,000</s_price></s_menu><s_sub_total><s_subtotal_price>230,000</s_price></s_menu><s_sub_total><s_subtotal_price>230,000</s_price></s_menu><s_sub_total><s_subtotal_price>230,000</s_price></s_menu><s_sub_total><s_subtotal_price>230,000</s_price></s_menu><s_sub_total><s_subtotal_price>230,000</s_price></s_menu><s_sub_total><s_subtotal_price>390,000</s_cashprice><s_changeprice>0</s_cnt><s_price>390,000</s_cashprice><s_changeprice>0</s_cnt><s_price>390,000</s_cashprice><s_changeprice>0</s_cnt><s_price>390,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>SOGOGI JAPCHAE</s_nm><s_cnt>1</s_cnt><s_price>150,000</s_price><sep/><s_nm>GONG GIBAB</s_nm><s_cnt>7</s_cnt><s_price>105,000</s_price><sep/><s_nm>CHULPAN CHEESE DAK GALBI</s_nm><s_cnt>1</s_cnt><s_price>230,000</s_price><sep/><s_nm>CREAM TEOK PO KI</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>EL KEUN HWANGTAE</s_nm><s_cnt>1</s_cnt><s_price>120,000</s_price><sep/><s_nm>SUNDUBU(TUKBEGI) CHAM KKOT SAL</s_nm><s_cnt>2</s_cnt><s_price>620,000</s_price><sep/><s_nm>U SAM GYEOP</s_nm><s_cnt>2</s_cnt><s_price>290,000</s_price><sep/><s_nm>U SEOL</s_nm><s_cnt>2</s_cnt><s_price>390,000</s_price><sep/><s_nm>U SAM GYEOP</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>ICE COFFE MIX</s_nm><s_cnt>3</s_cnt><s_price>0</s_price><sep/><s_nm>ICE BLACK COFFE</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>2,000,000</s_subtotal_price><s_discount_price>0</s_discount_price><s_service_price>140,000</s_service_price><s_tax_price>212,460</s_tax_price></s_sub_total><s_total><s_total_price>2,352,460</s_total_price><s_changeprice>0</s_changeprice><s_creditcardprice>2,352,460</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.5826839826839827\n",
+            "Prediction: <s_menu><s_nm>STIX CINNAMON</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price></s_menu><s_sub_total><s_subtotal_price>19,000</s_unitprice><s_cnt>1</s_cnt><s_price>19,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_total_price><s_cashprice>17,000</s_cashprice><s_changeprice>53,000</s_total_price><s_cashprice>53,000</s_total_price><s_cashprice>1851</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>STIX CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>CINNAMON SUGAR</s_nm><s_unitprice>17,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_price><sep/><s_nm>TRIPPLE CHEESE</s_nm><s_unitprice>17,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_price></s_menu><s_sub_total><s_subtotal_price>53,000</s_subtotal_price></s_sub_total><s_total><s_total_price>53,000</s_total_price><s_changeprice>0</s_changeprice><s_creditcardprice>53,000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.3838951310861423\n",
+            "Prediction: <s_menu><s_nm>ROTI UNYIL</s_nm><s_cnt>170</s_nm><s_cnt>272.000</s_price></s_menu><s_sub_total><s_subtotal_price>272.000</s_price></s_menu><s_sub_total><s_subtotal_price>6.000</s_price></s_menu><s_sub_total><s_subtotal_price>278.000</s_total_price><s_cashprice>300.000</s_cashprice><s_changeprice>22.000</s_total_price><s_cashprice>171</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>ROTI UNYIL</s_nm><s_cnt>170</s_cnt><s_price>272.000</s_price><sep/><s_nm>PAPER BAG BESAR</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price></s_menu><s_total><s_total_price>278.000</s_total_price><s_cashprice>300.000</s_cashprice><s_changeprice>22.000</s_changeprice><s_menuqty_cnt>171</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.29444444444444445\n",
+            "Prediction: <s_menu><s_nm>THAI ICED TEA (L)</s_nm><s_cnt>1</s_cnt><s_price>16,363</s_price></s_menu><s_sub_total><s_subtotal_price>16,36</s_subtotal_price></s_sub_total><s_total><s_total_price>1</s_cnt><s_price>16,999</s_total_price><s_cashprice>16,999</s_total_price><s_cashprice>16,9</s_tax_price></s_sub_total><s_total><s_total_price>17,999</s_total_price><s_cashprice>16,9</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>THAI ICED TEA (L)</s_nm><s_unitprice>16,363</s_unitprice><s_cnt>1</s_cnt><s_price>16.363</s_price></s_menu><s_sub_total><s_subtotal_price>16.363</s_subtotal_price><s_tax_price>1,636</s_tax_price></s_sub_total><s_total><s_total_price>17,999</s_total_price><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.35128205128205126\n",
+            "Prediction: <s_menu><s_nm>AOP Seafood</s_nm><s_cnt>1</s_cnt><s_price>85,000</s_price></s_menu><s_sub_total><s_subtotal_price>0murice Katsu Curry</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price></s_menu><s_sub_total><s_subtotal_price>35,000</s_price></s_menu><s_sub_total><s_subtotal_price>25,000</s_price></s_menu><s_sub_total><s_subtotal_price>240,000</s_total_price><s_cashprice>21,600</s_total_price><s_cashprice>26,160</s_cashprice><s_changeprice>287,7,760</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>AOP Seafood</s_nm><s_cnt>1</s_cnt><s_price>85,000</s_price><sep/><s_nm>Omurice Katsu Curry</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>Earl Gray Tea</s_nm><s_cnt>1</s_cnt><s_price>35,000</s_price><sep/><s_nm>Hot Tea</s_nm><s_cnt>1</s_cnt><s_price>25,000</s_price></s_menu><s_sub_total><s_subtotal_price>240,000</s_subtotal_price><s_service_price>21,600</s_service_price><s_tax_price>26,160</s_tax_price></s_sub_total><s_total><s_total_price>287,760</s_total_price></s_total>\n",
+            " Normed ED: 0.32803180914512925\n",
+            "Prediction: <s_menu><s_nm>MARBLE CASTELA</s_nm><s_cnt>22,000</s_unitprice><s_cnt>1</s_cnt><s_price>22,000</s_unitprice><s_cnt>1</s_cnt><s_price>22,000</s_subtotal_price></s_sub_total><s_total><s_total_price>22,000</s_total_price><s_cashprice>22,000</s_total_price><s_cashprice>22,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>MARBLE CASTELA</s_nm><s_unitprice>22,000</s_unitprice><s_cnt>1</s_cnt><s_price>22,000</s_price></s_menu><s_total><s_total_price>22,000</s_total_price><s_cashprice>22,000</s_cashprice><s_changeprice>0</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.29357798165137616\n",
+            "Prediction: <s_menu><s_nm>Seaweed Chicken</s_nm><s_cnt>1</s_cnt><s_price>42,000</s_price></s_menu><s_sub_total><s_subtotal_price>42,000</s_price></s_menu><s_sub_total><s_subtotal_price>42,000</s_subtotal_price></s_sub_total><s_total><s_total_price>42,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>8,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Seaweed Chicken</s_nm><s_cnt>1</s_cnt><s_price>42,000</s_price><s_sub><s_nm>- Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>42,000</s_subtotal_price></s_sub_total><s_total><s_total_price>42,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>8,000</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.2051948051948052\n",
+            "Prediction: <s_menu><s_nm>SB OR</s_nm><s_cnt>1</s_cnt><s_price>28,636</s_price></s_menu><s_sub_total><s_subtotal_price>Chokocha Flt</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>55,908</s_subtotal_price><s_tax_price>5,592</s_total_price><s_cashprice>61,500</s_total_price><s_cashprice>70,000</s_cashprice><s_changeprice>8,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>SB 1 OR</s_nm><s_cnt>1</s_cnt><s_price>28,636</s_price><sep/><s_nm>Chokocha Flt</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price><sep/><s_nm>Bbq Bento</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>55,908</s_subtotal_price><s_tax_price>5,592</s_tax_price></s_sub_total><s_total><s_total_price>61,500</s_total_price><s_cashprice>70,000</s_cashprice><s_changeprice>8,500</s_changeprice><s_menuqty_cnt>3</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.2698744769874477\n",
+            "Prediction: <s_menu><s_nm>52.000</s_unitprice><s_cnt>1x</s_cnt><s_price>52.000</s_unitprice><s_cnt>1x</s_cnt><s_price>52.000</s_unitprice><s_cnt>1x</s_cnt><s_price>52.000</s_unitprice><s_cnt>1x</s_cnt><s_price>22.000</s_unitprice><s_cnt>1x</s_cnt><s_price>22.000</s_unitprice><s_cnt>1x</s_cnt><s_price>22.000</s_unitprice><s_cnt>74.000</s_total_price><s_cashprice>7.400</s_total_price><s_cashprice>81-400</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Nasi CampurBali</s_nm><s_unitprice>52.000</s_unitprice><s_cnt>1x</s_cnt><s_price>52.000</s_price><sep/><s_nm>Lemon</s_nm><s_unitprice>22.000</s_unitprice><s_cnt>1x</s_cnt><s_price>22.000</s_price></s_menu><s_sub_total><s_subtotal_price>74.000</s_subtotal_price><s_tax_price>7.400</s_tax_price></s_sub_total><s_total><s_cashprice>81.400</s_cashprice></s_total>\n",
+            " Normed ED: 0.38169642857142855\n",
+            "Prediction: <s_menu><s_nm>CHOCOLATE ECLAIRIN</s_nm><s_cnt>26,000</s_price></s_menu><s_total><s_total_price>26,000</s_total_price><s_cashprice>25,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>CHOCOLATE ECLAIR</s_nm><s_cnt>2</s_cnt><s_price>26,000</s_price></s_menu><s_total><s_total_price>26,000</s_total_price><s_cashprice>26,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.10096153846153846\n",
+            "Prediction: <s_menu><s_nm>118 Round Wagyu (1gr)</s_nm><s_cnt>1</s_cnt><s_price>47.200</s_price></s_menu><s_sub_total><s_subtotal_price>10.000</s_price></s_menu><s_total><s_total_price>57.200</s_total_price><s_cashprice>57.200</s_cashprice><s_changeprice>57.200</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Round Wagyu (1gr)</s_nm><s_cnt>118</s_cnt><s_price>47.200</s_price><sep/><s_nm>Wagyu Rice Box</s_nm><s_cnt>1</s_cnt><s_price>10.000</s_price></s_menu><s_sub_total><s_subtotal_price>57.200</s_subtotal_price></s_sub_total><s_total><s_total_price>57.200</s_total_price><s_creditcardprice>57.200</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.31343283582089554\n",
+            "Prediction: <s_menu><s_nm>KENTHIR</s_nm><s_cnt>2</s_cnt><s_price>42.000</s_price></s_menu><s_sub_total><s_subtotal_price>6.000</s_price></s_menu><s_sub_total><s_subtotal_price>8.000</s_subtotal_price></s_sub_total><s_total><s_total_price>56.000</s_total_price><s_cashprice>56.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>KENTHIR 2</s_nm><s_cnt>2</s_cnt><s_price>42.000</s_price><sep/><s_nm>KOL GORENG</s_nm><s_cnt>2</s_cnt><s_price>6.000</s_price><sep/><s_nm>TEH MANIS</s_nm><s_cnt>2</s_cnt><s_price>8.000</s_price></s_menu><s_sub_total><s_subtotal_price>56.000</s_subtotal_price></s_sub_total><s_total><s_total_price>56.000</s_total_price><s_cashprice>56.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.24754901960784315\n",
+            "Prediction: <s_menu><s_nm>Lar ge</s_nm><s_cnt>1</s_cnt><s_price>11.000</s_price></s_menu><s_total><s_total_price>11.000</s_unitprice><s_cnt>1</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>20.000</s_price></s_menu><s_sub_total><s_subtotal_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>31.000</s_total_price><s_cashprice>40.000</s_cashprice><s_changeprice>9.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Large 1</s_nm><s_cnt>1</s_cnt><s_price>11.000</s_price><s_sub><s_nm>*Rhum</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub><sep/><s_nm>Pastry Keju</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price><s_sub><s_nm>*Plastik kcl</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_total><s_total_price>31.000</s_total_price><s_cashprice>40.000</s_cashprice><s_changeprice>9.000</s_changeprice><s_menuqty_cnt>4</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.36585365853658536\n",
+            "Prediction: <s_menu><s_nm>4003-Blueberry Fuji</s_nm><s_cnt>4003-</s_cnt><s_price>40.000</s_price></s_menu><s_sub_total><s_subtotal_price>x 1</s_cnt><s_price>40.000</s_price></s_menu><s_total><s_total_price>6001-Plastic Bag Small</s_nm><s_cnt>0</s_nm><s_cnt>x 1</s_cnt><s_price>0</s_tax_price></s_sub_total><s_total><s_total_price>2</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>4003-Blueberry Fuji</s_nm><s_unitprice>40.000</s_unitprice><s_cnt>x1</s_cnt><s_price>40.000</s_price><sep/><s_nm>6001-Plastic Bag Small</s_nm><s_unitprice>0</s_unitprice><s_cnt>x1</s_cnt><s_price>0</s_price></s_menu><s_total><s_total_price>40.000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>10.000</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.47164948453608246\n",
+            "Prediction: <s_menu><s_nm>Cha Keaw</s_nm><s_cnt>1</s_cnt><s_price>60.000</s_price></s_menu><s_sub_total><s_subtotal_price>60.000</s_cashprice><s_changeprice>60.000</s_cashprice><s_changeprice>60.000</s_cashprice><s_changeprice>60.000</s_cashprice><s_changeprice>60.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Cha Keaw L...</s_nm><s_cnt>x2</s_cnt><s_price>60.000</s_price><sep/><s_nm>Cha Keaw L...</s_nm><s_cnt>x2</s_cnt><s_discountprice>60.000)</s_discountprice><s_price>60.000</s_price></s_menu><s_total><s_total_price>60.000</s_total_price><s_creditcardprice>60.000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.40397350993377484\n",
+            "Prediction: <s_menu><s_nm>Thai Iced T.x」</s_cnt><s_price>20.000</s_price></s_menu><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Thai Iced T. .x1</s_nm><s_price>20.000</s_price></s_menu><s_sub_total><s_subtotal_price>20.000</s_subtotal_price></s_sub_total><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.2862595419847328\n",
+            "Prediction: <s_menu><s_nm>SEAFOOD MARINARA</s_nm><s_cnt>1</s_cnt><s_price>85,000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>85,500</s_price></s_menu><s_sub_total><s_subtotal_price>247,500</s_total_price><s_cashprice>14,850</s_cashprice><s_changeprice>PB16</s_creditcardprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>SEAFOOD MARINARA</s_nm><s_cnt>1</s_cnt><s_price>85,000</s_price><sep/><s_nm>CREAMY MARINARA SALMON</s_nm><s_cnt>1</s_cnt><s_price>85.500</s_price><sep/><s_nm>LYCHEE ICE TEA</s_nm><s_cnt>2</s_cnt><s_price>77,000</s_price></s_menu><s_sub_total><s_subtotal_price>247,500</s_subtotal_price><s_service_price>14,850</s_service_price><s_tax_price>26,235</s_tax_price></s_sub_total><s_total><s_total_price>288,585</s_total_price></s_total>\n",
+            " Normed ED: 0.43820224719101125\n",
+            "Prediction: <s_menu><s_nm>Viet Milk Coffee</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price></s_menu><s_total><s_total_price>+Hot</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_total_price><s_cashprice>25.000</s_total_price><s_cashprice>Rp 0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Viet Milk Coffee</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price><s_sub><s_nm>+Hot</s_nm><sep/><s_nm>+M</s_nm></s_sub></s_menu><s_sub_total><s_subtotal_price>25.000</s_subtotal_price></s_sub_total><s_total><s_total_price>25.000</s_total_price><s_cashprice>25.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.3413897280966767\n",
+            "Prediction: <s_menu><s_nm>XLB Org Pork 10x</s_nm><s_cnt>1</s_cnt><s_price>78,000</s_price></s_menu><s_sub_total><s_subtotal_price>65,000</s_price></s_menu><s_sub_total><s_subtotal_price>58,000</s_price></s_menu><s_sub_total><s_subtotal_price>DF Fish Fillet Garic</s_nm><s_cnt>1</s_cnt><s_price>108,000</s_price></s_menu><s_sub_total><s_subtotal_price>88,000</s_price></s_menu><s_sub_total><s_subtotal_price>38,000</s_total_price><s_cashprice>38,000</s_cashprice><s_changeprice>42,000</s_cashprice><s_changeprice>60,394</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>XLB Org Pork 10x</s_nm><s_cnt>1</s_cnt><s_price>78,000</s_price><sep/><s_nm>Sicito Babi</s_nm><s_cnt>1</s_cnt><s_price>65,000</s_price><sep/><s_nm>Hotplate Tahu</s_nm><s_cnt>1</s_cnt><s_price>58,000</s_price><sep/><s_nm>DF Fish Fillet Garlc</s_nm><s_cnt>1</s_cnt><s_price>108,000</s_price><sep/><s_nm>LM Pork Belly</s_nm><s_cnt>1</s_cnt><s_price>88,000</s_price><sep/><s_nm>Siew Mai</s_nm><s_cnt>1</s_cnt><s_price>38,800</s_price><sep/><s_nm>Kwan Yin Cup</s_nm><s_cnt>5</s_cnt><s_price>50,000</s_price><sep/><s_nm>Herbal Jelly</s_nm><s_cnt>1</s_cnt><s_price>38,000</s_price><sep/><s_nm>Onde-Onde</s_nm><s_cnt>1</s_cnt><s_price>38,000</s_price></s_menu><s_sub_total><s_subtotal_price>561,800</s_subtotal_price><s_service_price>42,135</s_service_price><s_tax_price>60,394</s_tax_price></s_sub_total><s_total><s_total_price>664,329</s_total_price><s_menuqty_cnt>13</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.5460599334073252\n",
+            "Prediction: <s_menu><s_nm>VANILLA CHOCO HEART CAKE</s_nm><s_cnt>1</s_cnt><s_price>180,000</s_price></s_menu><s_total><s_total_price>180,000</s_total_price><s_cashprice>180,000</s_cashprice><s_changeprice>\n",
+            "    Answer: <s_menu><s_nm>VANILLA CHOCO HEART CAKE</s_nm><s_cnt>1</s_cnt><s_price>180,000</s_price></s_menu><s_total><s_total_price>180,000</s_total_price><s_creditcardprice>180,000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.1407035175879397\n",
+            "Prediction: <s_menu><s_nm>Copuluire Cho ulate</s_nm><s_cnt>1</s_cnt><s_price>4,500</s_price></s_menu><s_sub_total><s_subtotal_price>4,500</s_price></s_menu><s_sub_total><s_subtotal_price>4,500</s_price></s_menu><s_sub_total><s_subtotal_price>4,500</s_price></s_menu><s_sub_total><s_subtotal_price>3,000</s_subtotal_price><s_tax_price>3,000</s_subtotal_price><s_tax_price>7,500</s_total_price><s_cashprice>(10%)</s_nm><s_cnt>8,250</s_total_price><s_cashprice>10,000</s_cashprice><s_changeprice>50</s_changeprice><s_menuqty_cnt>1,800</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Populaire Chocolate</s_nm><s_unitprice>4,500</s_unitprice><s_cnt>1</s_cnt><s_price>4,500</s_price><sep/><s_nm>Paddle Pop Choco Magma</s_nm><s_unitprice>3,000</s_unitprice><s_cnt>1</s_cnt><s_price>3,000</s_price></s_menu><s_sub_total><s_subtotal_price>7,500</s_subtotal_price><s_tax_price>750</s_tax_price></s_sub_total><s_total><s_total_price>8,250</s_total_price><s_total_etc>50</s_total_etc><s_cashprice>10,000</s_cashprice><s_changeprice>1,800</s_changeprice></s_total>\n",
+            " Normed ED: 0.381651376146789\n",
+            "Prediction: <s_menu><s_nm>French Fries</s_nm><s_cnt>1</s_cnt><s_price>10,909</s_price></s_menu><s_sub_total>2,0000</s_unitprice><s_cnt>2</s_cnt><s_price>36,364</s_price></s_menu><s_sub_total><s_subtotal_price>9,091</s_price></s_menu><s_sub_total><s_subtotal_price>5,636</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>38,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>French Fries</s_nm><s_cnt>1</s_cnt><s_price>10,909</s_price><sep/><s_nm>Cheese Burger</s_nm><s_cnt>2</s_cnt><s_price>36,364</s_price><sep/><s_nm>Milo</s_nm><s_cnt>1</s_cnt><s_price>9.091</s_price></s_menu><s_sub_total><s_subtotal_price>56,364</s_subtotal_price><s_tax_price>5,636</s_tax_price></s_sub_total><s_total><s_total_price>62,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>38,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.30580357142857145\n",
+            "Prediction: <s_menu><s_nm>ISI CAMPUR</s_nm><s_cnt>1</s_cnt><s_price>43.636</s_price></s_menu><s_sub_total><s_subtotal_price>43.636</s_price></s_menu><s_sub_total><s_subtotal_price>8.000</s_subtotal_price></s_sub_total><s_total><s_total_price>8.000</s_total_price><s_cashprice>51,636</s_subtotal_price></s_sub_total><s_total><s_total_price>5,164</s_total_price><s_cashprice>56,800</s_total_price><s_cashprice>110.000</s_cashprice><s_changeprice>53,200</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>ISI CAMPUR</s_nm><s_unitprice>43,636</s_unitprice><s_cnt>1</s_cnt><s_price>43.636</s_price><sep/><s_nm>A.MINERAL BOTOL</s_nm><s_unitprice>8.000</s_unitprice><s_cnt>1</s_cnt><s_price>8.000</s_price></s_menu><s_sub_total><s_subtotal_price>51,636</s_subtotal_price><s_tax_price>5,164</s_tax_price></s_sub_total><s_total><s_total_price>56,800</s_total_price><s_cashprice>110,000</s_cashprice><s_changeprice>53.200</s_changeprice></s_total>\n",
+            " Normed ED: 0.3857758620689655\n",
+            "Prediction: <s_menu><s_nm>WHOLE WHEAT PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_cashprice><s_changeprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>WHOLE WHEAT PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.0410958904109589\n",
+            "Prediction: <s_menu><s_nm>BASO TAHU</s_nm><s_cnt>1</s_cnt><s_price>43.6</s_price></s_menu><s_sub_total><s_subtotal_price>43.636</s_price></s_menu><s_sub_total><s_subtotal_price>43.636</s_price></s_menu><s_sub_total><s_subtotal_price>6.000</s_unitprice><s_cnt>1</s_cnt><s_price>49.636</s_subtotal_price></s_sub_total><s_total><s_total_price>4.96</s_total_price><s_cashprice>54.600</s_total_price><s_cashprice>60.100</s_total_price><s_cashprice>5.500</s_cashprice><s_changeprice>Terima</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>BASO TAHU</s_nm><s_unitprice>43.636</s_unitprice><s_cnt>1</s_cnt><s_price>43.636</s_price><sep/><s_nm>NASI PUTIH</s_nm><s_unitprice>6.000</s_unitprice><s_cnt>1</s_cnt><s_price>6.000</s_price></s_menu><s_sub_total><s_subtotal_price>49.636</s_subtotal_price><s_tax_price>4.964</s_tax_price></s_sub_total><s_total><s_total_price>54.600</s_total_price><s_cashprice>60.100</s_cashprice><s_changeprice>5.500</s_changeprice></s_total>\n",
+            " Normed ED: 0.3927893738140417\n",
+            "Prediction: <s_menu><s_nm>AIR MINERAL</s_nm><s_cnt>7,000</s_price></s_menu><s_total><s_total_price>7,000</s_total_price><s_cashprice>7,000</s_cashprice><s_changeprice>7,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>AIR MINERAL</s_nm><s_price>7,000</s_price></s_menu><s_total><s_total_price>7,000</s_total_price><s_cashprice>7,000</s_cashprice></s_total>\n",
+            " Normed ED: 0.22043010752688172\n",
+            "Prediction: <s_menu><s_nm>PAKET BER2</s_nm><s_cnt>1</s_cnt><s_price>69,091</s_price></s_menu><s_sub_total><s_subtotal_price>PAKET BER2</s_nm><s_cnt>1</s_cnt><s_price>69,091</s_subtotal_price></s_sub_total><s_total><s_total_price>69,909</s_tax_price></s_sub_total><s_total><s_total_price>76,000</s_total_price><s_cashprice>76,000</s_total_price><s_cashprice>76,000</s_cashprice><s_changeprice>76,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>PAKET BER2</s_nm><s_cnt>1</s_cnt><s_price>69,091</s_price><s_sub><s_nm>BREAD N CHEESE DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>MAC N CHEESE DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>PEPSI DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>P/P THUOSAND ISL DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>LIPTON ICE TEA DEL</s_nm><s_cnt>1</s_cnt></s_sub></s_menu><s_sub_total><s_subtotal_price>69,091</s_subtotal_price><s_tax_price>6,909</s_tax_price></s_sub_total><s_total><s_total_price>76,000</s_total_price></s_total>\n",
+            " Normed ED: 0.5059523809523809\n",
+            "Prediction: <s_menu><s_nm>Honey Mandarin</s_nm><s_cnt>2X</s_cnt><s_price>13,000</s_price></s_menu><s_sub_total><s_subtotal_price>26,000</s_price></s_menu><s_total><s_total_price>26,000</s_total_price><s_cashprice>30,000</s_cashprice><s_changeprice>4,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Honey Mandarin</s_nm><s_unitprice>13,000</s_unitprice><s_cnt>2 X</s_cnt><s_price>26,000</s_price></s_menu><s_total><s_total_price>26,000</s_total_price><s_cashprice>30,000</s_cashprice><s_changeprice>4,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.15730337078651685\n",
+            "Prediction: <s_menu><s_nm>SOTO MEDAN+NASI</s_nm><s_cnt>1</s_cnt><s_price>59.500</s_price></s_menu><s_sub_total><s_subtotal_price>GADO-GRDO</s_nm><s_cnt>1</s_cnt><s_price>34.500</s_price></s_menu><s_sub_total><s_subtotal_price>57.500</s_price></s_menu><s_sub_total><s_subtotal_price>151.500</s_total_price><s_cashprice>7.575</s_total_price><s_cashprice>15.908</s_cashprice><s_changeprice>174.983</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>SOTO MEDAN+NASI</s_nm><s_cnt>1</s_cnt><s_price>59.500</s_price><sep/><s_nm>GADO-GADO</s_nm><s_cnt>1</s_cnt><s_price>34.500</s_price><sep/><s_nm>SOTO BETAWI + NASI</s_nm><s_cnt>1</s_cnt><s_price>57.500</s_price></s_menu><s_sub_total><s_subtotal_price>151.500</s_subtotal_price><s_service_price>7.575</s_service_price><s_tax_price>15.908</s_tax_price></s_sub_total><s_total><s_total_price>174.983</s_total_price></s_total>\n",
+            " Normed ED: 0.31105990783410137\n",
+            "Prediction: <s_menu><s_nm>KaraageCurryTeishoku</s_nm><s_cnt>1</s_cnt><s_price>69,000</s_price></s_menu><s_total><s_total_price>19,000</s_cashprice><s_changeprice>15,000</s_total_price><s_cashprice>103,000</s_cashprice><s_changeprice>7,725</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>KaraageCurryTeishoku</s_nm><s_cnt>1</s_cnt><s_price>69,000</s_price><sep/><s_nm>Lemon Plate</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>Ocha Hot</s_nm><s_cnt>1</s_cnt><s_price>15,000</s_price></s_menu><s_sub_total><s_subtotal_price>103,000</s_subtotal_price><s_service_price>7,725</s_service_price><s_tax_price>11,073</s_tax_price></s_sub_total><s_total><s_total_price>121,798</s_total_price><s_menutype_cnt>3</s_menutype_cnt><s_menuqty_cnt>3</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.5734406438631791\n",
+            "Prediction: <s_menu><s_nm>Dum Dum Thai Coffee</s_nm><s_cnt>1</s_cnt><s_price>19.000</s_price></s_menu><s_total><s_total_price>1.000</s_total_price><s_cashprice>20.000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>30.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Dum Dum Thai Coffee</s_nm><s_cnt>1</s_cnt><s_price>19.000</s_price><s_sub><s_nm>Ice</s_nm><s_cnt>1</s_cnt><s_price>1.000</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>20.000</s_subtotal_price></s_sub_total><s_total><s_total_price>20.000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>30.000</s_changeprice></s_total>\n",
+            " Normed ED: 0.3081232492997199\n",
+            "Prediction: <s_menu><s_nm>STIX CINNAMON</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price></s_menu><s_sub_total><s_subtotal_price>19,000</s_unitprice><s_cnt>1</s_cnt><s_price>19,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_total_price><s_cashprice>36,000</s_total_price><s_cashprice>4607</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>STIX CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><s_cnt>1 x</s_cnt><s_price>19,000</s_price><sep/><s_nm>TRIPPLE CHEESE</s_nm><s_unitprice>17,000</s_unitprice><s_cnt>1 x</s_cnt><s_price>17,000</s_price></s_menu><s_sub_total><s_subtotal_price>36,000</s_subtotal_price></s_sub_total><s_total><s_total_price>36,000</s_total_price><s_changeprice>0</s_changeprice><s_creditcardprice>36,000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.419953596287703\n",
+            "Prediction: <s_menu><s_nm>ICED TT</s_nm><s_cnt>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_cashprice><s_changeprice>50,000</s_cashprice><s_changeprice>50,000</s_cashprice><s_changeprice>.30,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>ICED TT</s_nm><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>30,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.2072072072072072\n",
+            "Prediction: <s_menu><s_nm>THAI ICED TEA</s_nm><s_cnt>1</s_cnt><s_price>@20.000</s_unitprice><s_cnt>1</s_cnt><s_price>20.000</s_unitprice><s_cnt>1</s_cnt><s_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>THAI ICED TEA</s_nm><s_unitprice>@20.000</s_unitprice><s_cnt>1</s_cnt><s_price>20.000</s_price></s_menu><s_sub_total><s_subtotal_price>20.000</s_subtotal_price></s_sub_total><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.28802588996763756\n",
+            "Prediction: <s_menu><s_nm>KFC Winger HC</s_nm><s_cnt>2</s_cnt><s_price>40,000</s_price></s_menu><s_sub_total><s_subtotal_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>5,909</s_price></s_menu><s_sub_total><s_subtotal_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>9</s_cnt><s_price>60,454</s_price></s_menu><s_sub_total><s_subtotal_price>6,046</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>33,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>KFC Winger HC</s_nm><s_cnt>2</s_cnt><s_price>40,000</s_price><sep/><s_nm>Ori Bento</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price><sep/><s_nm>Mango Float</s_nm><s_cnt>1</s_cnt><s_price>5,909</s_price><sep/><s_nm>F.Wngr GES-HC</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>CHARGE TA</s_nm><s_cnt>1</s_cnt><s_price>909</s_price></s_menu><s_sub_total><s_subtotal_price>60,454</s_subtotal_price><s_tax_price>6,046</s_tax_price></s_sub_total><s_total><s_total_price>66,500</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>33,500</s_changeprice><s_menuqty_cnt>6</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.3656957928802589\n",
+            "Prediction: <s_menu><s_nm>Enting2 Dua Bandeng Ori</s_nm><s_cnt>1</s_cnt><s_price>31.000</s_price></s_menu><s_sub_total><s_subtotal_price>31.000</s_unitprice><s_cnt>1</s_cnt><s_price>68.000</s_price></s_menu><s_sub_total><s_subtotal_price>99.000</s_cashprice><s_changeprice>99.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Enting2 Dua Bandeng Ori</s_nm><s_num>01069</s_num><s_unitprice>31.000</s_unitprice><s_cnt>1</s_cnt><s_price>31.000</s_price><sep/><s_nm>TAHU BAKSO Grg Ayam VC [biji</s_nm><s_num>07165</s_num><s_unitprice>6.800</s_unitprice><s_cnt>10</s_cnt><s_price>68.000</s_price></s_menu><s_total><s_total_price>99.000</s_total_price><s_creditcardprice>99.000</s_creditcardprice><s_menutype_cnt>2</s_menutype_cnt><s_menuqty_cnt>11</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.46710526315789475\n",
+            "Prediction: <s_menu><s_nm>Cheese Tart</s_nm><s_cnt>*</s_cnt><s_price>Rp58000.00</s_price></s_menu><s_sub_total><s_subtotal_price>Rp58000.00</s_price></s_menu><s_sub_total><s_subtotal_price>Rp5272.73</s_subtotal_price></s_sub_total><s_total><s_total_price>Rp58000.00</s_total_price><s_cashprice>Rp58000.00</s_cashprice><s_changeprice>Rp100</s_tax_price></s_sub_total><s_total><s_total_price>Rp42000.00</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Cheese Tart</s_nm><s_cnt>*2</s_cnt><s_price>Rp 58000.00</s_price><s_sub><s_nm>Bag-S</s_nm><sep/><s_nm>PS Carrier</s_nm></s_sub></s_menu><s_sub_total><s_subtotal_price>Rp 58000.00</s_subtotal_price><s_tax_price>Rp 5272.73</s_tax_price></s_sub_total><s_total><s_total_price>Rp 58000.00</s_total_price><s_cashprice>Rp 100000.00</s_cashprice><s_changeprice>Rp 42000.00</s_changeprice></s_total>\n",
+            " Normed ED: 0.37681159420289856\n",
+            "Prediction: <s_menu><s_nm>Mineral Water</s_nm><s_cnt>2</s_cnt><s_price>18000</s_price></s_menu><s_sub_total><s_subtotal_price>1</s_cnt><s_price>11.000</s_price></s_menu><s_sub_total><s_subtotal_price>11.000</s_price></s_menu><s_sub_total><s_subtotal_price>9000</s_subtotal_price></s_sub_total><s_total><s_total_price>154,000</s_total_price><s_cashprice>100</s_total_price><s_cashprice>16 170</s_total_price><s_cashprice>177.870</s_total_price><s_cashprice>177.870</s_total_price><s_cashprice>177.870</s_cashprice><s_changeprice>\n",
+            "    Answer: <s_menu><s_nm>Mineral Water</s_nm><s_cnt>2</s_cnt><s_price>18 000</s_price><sep/><s_nm>Teh Tawar Dingin</s_nm><s_cnt>1</s_cnt><s_price>11.000</s_price><sep/><s_nm>Soto Betawi</s_nm><s_cnt>2</s_cnt><s_price>116.000</s_price><sep/><s_nm>NASI PUTIH</s_nm><s_cnt>1</s_cnt><s_price>9.000</s_price></s_menu><s_sub_total><s_subtotal_price>154 000</s_subtotal_price><s_service_price>7 700</s_service_price><s_tax_price>16 170</s_tax_price></s_sub_total><s_total><s_total_price>177.870</s_total_price><s_menuqty_cnt>6</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.4250936329588015\n",
+            "Prediction: <s_menu><s_nm>Crab Stick</s_nm><s_cnt>1</s_cnt><s_price>9.000</s_price></s_menu><s_sub_total><s_subtotal_price>10.000</s_price></s_menu><s_sub_total><s_subtotal_price>7.000</s_price></s_menu><s_sub_total><s_subtotal_price>8.000</s_price></s_menu><s_sub_total><s_subtotal_price>2</s_cnt><s_price>24.000</s_total_price><s_cashprice>6.000</s_total_price><s_cashprice>72.000</s_cashprice><s_changeprice>72.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Crab Stick</s_nm><s_cnt>1</s_cnt><s_price>9.000</s_price><sep/><s_nm>Bakso Lobster</s_nm><s_cnt>1</s_cnt><s_price>10.000</s_price><sep/><s_nm>Sawi Putih</s_nm><s_cnt>1</s_cnt><s_price>7.000</s_price><sep/><s_nm>Jamur Enoki</s_nm><s_cnt>1</s_cnt><s_price>8.000</s_price><sep/><s_nm>Jamur Kuping</s_nm><s_cnt>1</s_cnt><s_price>8.000</s_price><sep/><s_nm>Maling</s_nm><s_unitprice>12000</s_unitprice><s_cnt>2</s_cnt><s_price>24.000</s_price><sep/><s_nm>Nasi (MLY)</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price></s_menu><s_sub_total><s_subtotal_price>72.000</s_subtotal_price></s_sub_total><s_total><s_total_price>72.000</s_total_price><s_creditcardprice>72.000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.5221112696148359\n",
+            "Prediction: <s_menu><s_nm>Sate Padang</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price></s_menu><s_total><s_total_price>25.000</s_total_price><s_cashprice>25.000</s_cashprice><s_changeprice>\n",
+            "    Answer: <s_menu><s_nm>Sate Padang</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price></s_menu><s_total><s_total_price>25.000</s_total_price><s_cashprice>25.000</s_cashprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.1724137931034483\n",
+            "Prediction: <s_menu><s_nm>SURIMI</s_nm><s_cnt>1</s_cnt><s_price>29,091</s_price></s_menu><s_sub_total><s_subtotal_price>CREAMY CHK CLS FTC</s_nm><s_cnt>1</s_cnt><s_price>42,727</s_price></s_menu><s_sub_total><s_subtotal_price>MIX 4FUN CHOCOLATE</s_nm><s_cnt>1</s_cnt><s_price>19,091</s_price></s_menu><s_sub_total><s_subtotal_price>60,909</s_price></s_menu><s_sub_total><s_subtotal_price>99,091</s_total_price><s_cashprice>250,909</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>SURIMI</s_nm><s_cnt>1</s_cnt><s_price>29,091</s_price><sep/><s_nm>CREAMY CHK CLS FTC</s_nm><s_cnt>1</s_cnt><s_price>42,727</s_price><sep/><s_nm>MIX 4FUN CHOCOLATE</s_nm><s_cnt>1</s_cnt><s_price>19,091</s_price><sep/><s_nm>GREEN ITSODA PITCHER</s_nm><s_cnt>1</s_cnt><s_price>60,909</s_price><sep/><s_nm>SC/R GRILLED STEAK</s_nm><s_cnt>1</s_cnt><s_price>99,091</s_price></s_menu><s_sub_total><s_subtotal_price>250,909</s_subtotal_price><s_tax_price>25,091</s_tax_price></s_sub_total><s_total><s_total_price>276,000</s_total_price></s_total>\n",
+            " Normed ED: 0.4438405797101449\n",
+            "Prediction: <s_menu><s_nm>PEARL CHOCO TEA</s_nm><s_cnt>1</s_cnt><s_price>17,000</s_price></s_menu><s_sub_total><s_subtotal_price>GREEN TEA LYCHEE</s_nm><s_cnt>1</s_cnt><s_price>18.000</s_price></s_menu><s_sub_total><s_subtotal_price>35.000</s_cashprice><s_changeprice>100.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>PEARL CHOCO TEA</s_nm><s_cnt>1</s_cnt><s_price>17.000</s_price><sep/><s_nm>GREEN TEA LYCHEE</s_nm><s_cnt>1</s_cnt><s_price>18.000</s_price><sep/><s_nm>TUTUP SEAL</s_nm><s_cnt>2</s_cnt><s_price>0</s_price><sep/><s_nm>CUP 14 OZ</s_nm><s_cnt>2</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>35.000</s_subtotal_price></s_sub_total><s_total><s_total_price>35.000</s_total_price><s_cashprice>100.000</s_cashprice><s_changeprice>65.000</s_changeprice><s_menuqty_cnt>6</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.5288461538461539\n",
+            "Prediction: <s_menu><s_nm>S-Milk tea</s_nm><s_cnt>@17,000</s_unitprice><s_cnt>1X</s_cnt><s_price>17,000</s_price></s_menu><s_total><s_total_price>17,000</s_total_price><s_cashprice>17,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>S-Milk tea</s_nm><s_unitprice>@17,000</s_unitprice><s_cnt>1X</s_cnt><s_price>17,000</s_price><s_sub><s_nm>100%</s_nm></s_sub></s_menu><s_sub_total><s_subtotal_price>17,000</s_subtotal_price><s_tax_price>0</s_tax_price></s_sub_total><s_total><s_total_price>17,000</s_total_price><s_cashprice>17,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.37329700272479566\n",
+            "Prediction: <s_menu><s_nm>HAZELNUT CHOCO MT ( R )</s_nm><s_cnt>1</s_cnt><s_price>24,000</s_price></s_menu><s_sub_total><s_subtotal_price>24,000</s_price></s_menu><s_sub_total><s_subtotal_price>24,000</s_subtotal_price></s_sub_total><s_total><s_total_price>2</s_cnt><s_price>2</s_cnt><s_price>2</s_cnt><s_price>2</s_cnt><s_price>2</s_cnt><s_price>2</s_cnt><s_price>52,000</s_total_price><s_cashprice>52,000</s_total_price><s_cashprice>52,000</s_total_price><s_cashprice>52,000</s_total_price><s_cashprice>52,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>HAZELNUT CHOCO MT (R)</s_nm><s_cnt>1 x</s_cnt><s_price>24,000</s_price><s_sub><s_nm>PEARL (R)</s_nm><s_price>4,000</s_price></s_sub><sep/><s_nm>HAZELNUT CHOCO MT (R)</s_nm><s_cnt>1 x</s_cnt><s_price>24,000</s_price></s_menu><s_sub_total><s_subtotal_price>52,000</s_subtotal_price></s_sub_total><s_total><s_total_price>52,000</s_total_price><s_creditcardprice>52,000</s_creditcardprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.4675090252707581\n",
+            "Prediction: <s_menu><s_nm>Peanut & Cheese</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>1,364</s_tax_price></s_sub_total><s_total><s_total_price>15,000</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>5,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Peanut & Cheese</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>13,636</s_subtotal_price><s_tax_price>1,364</s_tax_price></s_sub_total><s_total><s_total_price>15,000</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>5,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.09063444108761329\n",
+            "Prediction: <s_menu><s_nm>LEMONADE22OZ</s_nm><s_cnt>1</s_cnt><s_price>26,000</s_price></s_menu><s_sub_total><s_subtotal_price>26,000</s_price></s_menu><s_sub_total><s_subtotal_price>26,000</s_total_price><s_cashprice>26,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>LEMONADE22OZ</s_nm><s_cnt>1</s_cnt><s_price>26,000</s_price><s_sub><s_price>26,000</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>26,000</s_subtotal_price></s_sub_total><s_total><s_total_price>26,000</s_total_price><s_changeprice>0</s_changeprice><s_emoneyprice>26,000</s_emoneyprice></s_total>\n",
+            " Normed ED: 0.2893081761006289\n",
+            "Prediction: <s_menu><s_nm>M-Passion Fruit Mac</s_nm><s_cnt>1X</s_cnt><s_price>29,000</s_unitprice><s_cnt>1X</s_cnt><s_price>29,000</s_unitprice><s_cnt>1X</s_cnt><s_price>29,000</s_cashprice><s_changeprice>30,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>M-Passion Fruit Mac</s_nm><s_unitprice>@29,000</s_unitprice><s_cnt>1X</s_cnt><s_price>29,000</s_price><s_sub><s_nm>25%</s_nm><sep/><s_nm>Less Ice</s_nm></s_sub></s_menu><s_sub_total><s_subtotal_price>29,000</s_subtotal_price><s_tax_price>0</s_tax_price></s_sub_total><s_total><s_total_price>29,000</s_total_price><s_cashprice>30,000</s_cashprice><s_changeprice>1,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.4975369458128079\n",
+            "Prediction: <s_menu><s_nm>PAKET BER4 UP3</s_nm><s_cnt>1</s_cnt><s_price>154,545</s_price></s_menu><s_sub_total><s_subtotal_price>BREAD CHEESE DEL</s_nm><s_cnt>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>15</s_cnt><s_price>DEL</s_nm><s_cnt>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>154,545</s_total_price><s_cashprice>170,000</s_total_price><s_cashprice>170,000</s_total_price><s_cashprice>170,000</s_cashprice><s_changeprice>1</s_cnt><s_price>15,455</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>PAKET BER4 UP3</s_nm><s_cnt>1</s_cnt><s_price>154,545</s_price><s_sub><s_nm>BREAD N CHEESE DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>TUNA DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>CRABSTICK FUSILLI DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>LEMON TEA HANGAT DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>BLACKCURRANT DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SC/P THOUSAND IS DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SCSC/P BBQ BEEF DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>CR/P BEEF MAYO DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SUNRISE ITALIAN SODA</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SUNRISE ITALIAN SODA</s_nm><s_cnt>1</s_cnt></s_sub></s_menu><s_sub_total><s_subtotal_price>154,545</s_subtotal_price><s_tax_price>15,455</s_tax_price></s_sub_total><s_total><s_total_price>170,000</s_total_price></s_total>\n",
+            " Normed ED: 0.5075834175935288\n",
+            "Prediction: <s_menu><s_nm>1023-Chocochip & Walnut</s_nm><s_cnt>10</s_cnt><s_price>29,000</s_price></s_menu><s_sub_total><s_subtotal_price>29.000</s_price></s_menu><s_sub_total><s_subtotal_price>6001-Plastic Bag Small</s_nm><s_cnt>0</s_cnt><s_price>0</s_tax_price></s_sub_total><s_total><s_total_price>29.000</s_total_price><s_cashprice>100.000</s_cashprice><s_changeprice>71.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Chocochip & Walnut</s_nm><s_num>1023-</s_num><s_unitprice>29.000</s_unitprice><s_cnt>x1</s_cnt><s_price>29.000</s_price><sep/><s_nm>Plastic Bag Small</s_nm><s_num>6001-</s_num><s_unitprice>0</s_unitprice><s_cnt>x1</s_cnt><s_price>0</s_price></s_menu><s_total><s_total_price>29.000</s_total_price><s_cashprice>100.000</s_cashprice><s_changeprice>71.000</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.375886524822695\n",
+            "Prediction: <s_menu><s_nm>CINEMAXX CINEMAXX CINEL CINE REGULAR</s_nm><s_cnt>2</s_cnt><s_price>35000.00</s_price></s_menu><s_sub_total><s_subtotal_price>70000.00</s_price></s_menu><s_sub_total><s_subtotal_price>70000.00</s_cashprice><s_changeprice>CINEMAXX</s_nm><s_cnt>0.00</s_changeprice><s_menuqty_cnt>CINEMAXX</s_nm><s_cnt>2</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>REGULAR</s_nm><s_unitprice>35000.00</s_unitprice><s_cnt>2</s_cnt><s_price>70000.00</s_price></s_menu><s_total><s_total_price>70000.00</s_total_price><s_total_etc>70000.00</s_total_etc><s_changeprice>0.00</s_changeprice></s_total>\n",
+            " Normed ED: 0.4604105571847507\n",
+            "Prediction: <s_menu><s_nm>K7</s_nm><s_cnt>1217</s_nm><s_cnt>ADD</s_nm><s_cnt>12</s_cnt><s_price>39,091</s_price></s_menu><s_sub_total><s_subtotal_price>909</s_price></s_menu><s_total><s_total_price>40,000</s_total_price><s_cashprice>4,000</s_cashprice><s_changeprice>Rp.50,000</s_cashprice><s_changeprice>Rp.50,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>K7 1217</s_nm><s_price>39,091</s_price><s_sub><s_nm>ADD CHICKEN BOX</s_nm><s_price>909</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>40,000</s_subtotal_price><s_tax_price>4,000</s_tax_price></s_sub_total><s_total><s_total_price>44,000</s_total_price><s_cashprice>Rp. 50,000</s_cashprice><s_changeprice>Rp. 6,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.3453038674033149\n",
+            "Prediction: <s_menu><s_nm><FC Winger HC</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_cashprice><s_changeprice>25,000</s_cashprice><s_changeprice>2,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm><FC Winger HC</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price><sep/><s_nm>CHARGE TA</s_nm><s_cnt>1</s_cnt><s_price>909</s_price></s_menu><s_sub_total><s_subtotal_price>20,909</s_subtotal_price><s_tax_price>2,091</s_tax_price></s_sub_total><s_total><s_total_price>23,000</s_total_price><s_cashprice>25,000</s_cashprice><s_changeprice>2,000</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.31784841075794623\n",
+            "Prediction: <s_menu><s_nm>PAKET BER4</s_nm><s_cnt>1</s_cnt><s_price>138.182</s_price></s_menu><s_sub_total><s_subtotal_price>BREAD N CHEESE DEL</s_nm><s_cnt>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>DEL</s_nm><s_cnt>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>15,6</s_subtotal_price><s_tax_price>172,000</s_total_price><s_cashprice>172,000</s_total_price><s_cashprice>172,000</s_total_price><s_cashprice>172,000</s_total_price><s_cashprice>172,000</s_total_price><s_cashprice>172,000</s_total_price><s_cashprice>172,000</s_total_price><s_cashprice>172,000</s_total_price><s_cashprice>17</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>1</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>0</s_cnt><s_price>\n",
+            "    Answer: <s_menu><s_nm>PAKET BER4</s_nm><s_cnt>1</s_cnt><s_price>138,182</s_price><s_sub><s_nm>BREAD N CHEESE DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>BREAD N CHEESE DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>CRABSTICK FUSILLI DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>LIME SQUASH DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>LIME SQUASH DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>P/P SPICY TUNA DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>P/P THUOSAND ISL DEL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>P/P BEEF CORN</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SUNRISE ITALIAN SODA</s_nm><s_cnt>1</s_cnt><sep/><s_nm>LIPTON ICE TEA DEL</s_nm><s_cnt>1</s_cnt></s_sub><sep/><s_nm>50% CHICKEN ROYAL</s_nm><s_cnt>1</s_cnt><s_price>18,182</s_price></s_menu><s_sub_total><s_subtotal_price>156,364</s_subtotal_price><s_tax_price>15,636</s_tax_price></s_sub_total><s_total><s_total_price>172,000</s_total_price></s_total>\n",
+            " Normed ED: 0.8715419257988419\n",
+            "Prediction: <s_menu><s_nm>Emily's Shrimp Scampi</s_nm><s_cnt>1</s_cnt><s_price>69.000</s_price></s_menu><s_sub_total><s_subtotal_price>69.000</s_price></s_menu><s_sub_total><s_subtotal_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>SERVICE</s_nm><s_cnt>7.280</s_total_price><s_cashprice>+25</s_tax_price></s_sub_total><s_total><s_total_price>80.100</s_total_price><s_cashprice>80.100</s_total_price><s_cashprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Emily's Shrimp Scampi Fettucine</s_nm><s_cnt>1</s_cnt><s_price>69.000</s_price></s_menu><s_sub_total><s_subtotal_price>69.000</s_subtotal_price><s_discount_price>0</s_discount_price><s_service_price>3.795</s_service_price><s_etc>7.280<sep/>+25</s_etc></s_sub_total><s_total><s_total_price>80.100</s_total_price><s_total_etc>80.100</s_total_etc><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.3157894736842105\n",
+            "Prediction: <s_menu><s_nm>SAYOR</s_nm><s_cnt>1</s_cnt><s_price>13.6</s_price></s_menu><s_sub_total><s_subtotal_price>13.636</s_price></s_menu><s_sub_total><s_subtotal_price>27.27</s_subtotal_price></s_sub_total><s_total><s_total_price>2.700</s_total_price><s_cashprice>30,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>20,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>SAYAP</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price><sep/><s_nm>PAHA BAWAH</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>27,272</s_subtotal_price><s_tax_price>2,700</s_tax_price></s_sub_total><s_total><s_total_price>30,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>20,000</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.29310344827586204\n",
+            "Prediction: <s_menu><s_nm>Choco Cheese</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>-2,045</s_price></s_menu><s_sub_total><s_subtotal_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>-2,045</s_tax_price></s_sub_total><s_total><s_total_price>1,159</s_total_price><s_cashprice>12,750</s_total_price><s_cashprice>12,750</s_total_price><s_cashprice>12,750</s_cashprice><s_changeprice>12,750</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Choco Cheese</s_nm><s_unitprice>13,636</s_unitprice><s_cnt>1</s_cnt><s_discountprice>-2,045</s_discountprice></s_menu><s_sub_total><s_subtotal_price>13,636</s_subtotal_price><s_discount_price>-2,045</s_discount_price><s_tax_price>1,159</s_tax_price></s_sub_total><s_total><s_total_price>12,750</s_total_price><s_cashprice>12,750</s_cashprice></s_total>\n",
+            " Normed ED: 0.3868131868131868\n",
+            "Prediction: <s_menu><s_nm>Lemon Tea (L)</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price></s_menu><s_total><s_total_price>25.000</s_total_price><s_cashprice>30.000</s_cashprice><s_changeprice>5.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Lemon Tea (L)</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price></s_menu><s_total><s_total_price>25.000</s_total_price><s_cashprice>30.000</s_cashprice><s_changeprice>5.000</s_changeprice></s_total>\n",
+            " Normed ED: 0.0\n",
+            "Prediction: <s_menu><s_nm>Hulk Topper Package</s_nm><s_cnt>1</s_cnt><s_price>100.000</s_price></s_menu><s_total><s_total_price>100.000</s_total_price><s_cashprice>100.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Hulk Topper Package</s_nm><s_cnt>1</s_cnt><s_price>100.000</s_price></s_menu><s_total><s_total_price>100.000</s_total_price><s_cashprice>100.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.0\n",
+            "Prediction: <s_menu><s_nm>Giant Squid</s_nm><s_cnt>x」</s_cnt><s_price>Rp. 39.000</s_price></s_menu><s_sub_total><s_subtotal_price>Rp. 0</s_price></s_menu><s_sub_total><s_subtotal_price>Rp. 0</s_price></s_menu><s_sub_total><s_subtotal_price>Rp. 39.000</s_total_price><s_cashprice>Rp. 39.000</s_cashprice><s_changeprice>Rp. 50.000</s_cashprice><s_changeprice>Rp. 50.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Giant Squid</s_nm><s_cnt>x1</s_cnt><s_price>Rp. 39.000</s_price><s_sub><s_nm>C.Finishing - Cut</s_nm><s_price>Rp. 0</s_price><sep/><s_nm>B.Spicy Level - Extreme Hot</s_nm><s_price>Rp. 0</s_price><sep/><s_nm>A.Flavour- Salt & Pepper</s_nm><s_price>Rp. 0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>Rp. 39.000</s_subtotal_price></s_sub_total><s_total><s_total_price>Rp. 39.000</s_total_price><s_cashprice>Rp. 50.000</s_cashprice><s_changeprice>Rp. 11.000</s_changeprice></s_total>\n",
+            " Normed ED: 0.35445544554455444\n",
+            "Epoch 0:  40%|████      | 320/800 [01:47<02:40,  2.99it/s, v_num=1]"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n",
+            "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+            "To disable this warning, you can either:\n",
+            "\t- Avoid using `tokenizers` before the fork if possible\n",
+            "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Prediction: <s_menu><s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>PIZZA TOAST</s_nm><s_cnt>1</s_cnt><s_price>16,000</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>1</s_cnt><s_price>45,500</s_price></s_menu><s_total><s_total_price>4,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>4,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>PIZZA TOAST</s_nm><s_cnt>1</s_cnt><s_price>16,000</s_price></s_menu><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>4,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.16058394160583941\n",
+            "Prediction: <s_menu><s_nm>Kopi Susu Kolonel</s_nm><s_cnt>1</s_cnt><s_price>23.000</s_price><sep/><s_nm>Total</s_nm><s_price>23.000</s_price><sep/><s_nm>Tunai</s_nm><s_price>23.000</s_price><sep/><s_nm>Kembali</s_nm><s_price>23.000</s_price><sep/><s_nm>Tunai</s_nm><s_price>50.000</s_price><sep/><s_nm>Kembali 27.000</s_unitprice><s_cnt>1</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>Kopi Susu Kolonel</s_nm><s_cnt>1</s_cnt><s_price>23.000</s_price></s_menu><s_total><s_total_price>23.000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>27.000</s_changeprice></s_total>\n",
+            " Normed ED: 0.5014245014245015\n",
+            "Prediction: <s_menu><s_nm>S-Ovaltine</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price><sep/><s_nm>50%</s_nm><s_cnt>1</s_cnt><s_price>1,818</s_price><sep/><s_nm>PB1:</s_nm><s_price>18,181</s_price><sep/><s_nm>Subtotal:</s_nm><s_price>20,000</s_price><sep/><s_nm>Total:</s_nm><s_price>20,000</s_price><sep/><s_nm>Cash:</s_nm><s_price>100,000</s_price></s_menu><s_total><s_total_price>80,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>10%</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>S-Ovaltine 50%</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price><s_vatyn>10% Tax Included</s_vatyn></s_menu><s_sub_total><s_subtotal_price>18,181</s_subtotal_price><s_tax_price>1,818</s_tax_price></s_sub_total><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.44017094017094016\n",
+            "Prediction: <s_menu><s_nm>Black Tea</s_nm><s_cnt>1X</s_cnt><s_price>28,000</s_price><sep/><s_nm>M-Caramel Black Tea</s_nm><s_cnt>1X</s_cnt><s_price>28,000</s_price><sep/><s_nm>70%</s_nm><s_price>28,000</s_price><sep/><s_nm>Less Ice</s_nm><s_price>0-</s_price><sep/><s_nm>PB1:</s_nm><s_price>0-</s_price><sep/><s_nm>Subtotal:</s_nm><s_price>28,000</s_price><sep/><s_nm>Total:</s_nm><s_price>28,000</s_price><sep/><s_nm>Cash:</s_nm><s_price>28,000</s_price><sep/><s_nm>CHANGE:</s_nm><s_unitprice>28,000</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>M-Caramel Black Tea</s_nm><s_unitprice>@28,000</s_unitprice><s_cnt>1X</s_cnt><s_price>28,000</s_price><s_sub><s_nm>70%</s_nm><sep/><s_nm>Less Ice</s_nm></s_sub></s_menu><s_sub_total><s_subtotal_price>28,000</s_subtotal_price><s_tax_price>0</s_tax_price></s_sub_total><s_total><s_total_price>28,000</s_total_price><s_cashprice>28,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.4961089494163424\n",
+            "Prediction: <s_menu><s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><sep/><s_nm>- Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>ITEMS:1</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><sep/><s_nm>Total</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>-</s_cnt><s_price>0</s_price><sep/><s_nm>-</s_cnt><s_price>0</s_price><sep/><s_nm>ITEMS:1</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><sep/><s_nm>Total</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><sep/><s_nm>Cash 50.000</s_unitprice><s_cnt>1</s_cnt><s_price>9,000</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><s_sub><s_nm>Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>41,000</s_subtotal_price></s_sub_total><s_total><s_total_price>41,000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>:9,000</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.5175438596491229\n",
+            "Prediction: <s_menu><s_nm>LE MINERAL</s_nm><s_price>8,000</s_price><sep/><s_nm>1.00</s_unitprice><sep/><s_nm>NETI ANT</s_nm><s_price>7,273</s_price><sep/><s_nm>TAX AMT</s_nm><s_price>727</s_price><sep/><s_nm>TOTAL</s_nm><s_price>8,000</s_price><sep/><s_nm>CASH</s_nm><s_price>8,000</s_price></s_menu><s_total><s_total_price>8,000</s_total_price><s_cashprice>8,000</s_cashprice><s_changeprice>8,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>LE MINERAL</s_nm><s_cnt>1.00</s_cnt><s_price>8,000</s_price></s_menu><s_sub_total><s_subtotal_price>7,273</s_subtotal_price><s_tax_price>727</s_tax_price></s_sub_total><s_total><s_total_price>8,000</s_total_price><s_cashprice>8,000</s_cashprice></s_total>\n",
+            " Normed ED: 0.5085158150851582\n",
+            "Prediction: <s_menu><s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>OREO GREEN TEA SPREAD</s_nm><s_cnt>1</s_cnt><sep/><s_nm>WHITE CHOCO BANANA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price><sep/><s_nm>OREO GREEN TEA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price><sep/><s_nm>WHITE</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price><sep/><s_nm>WHITE CHOCO BANANA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>1</s_cnt><s_price>123,000</s_total_price><s_cashprice>123,000</s_cashprice><s_changeprice>123,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>OREO GREEN TEA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price><sep/><s_nm>WHITE CHOCO BANANA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price></s_menu><s_total><s_total_price>123,000</s_total_price><s_creditcardprice>123,000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.4555921052631579\n",
+            "Prediction: <s_menu><s_nm>Choco Devil</s_nm><s_price>63,636</s_price><sep/><s_nm>CP 360 Club Card</s_nm><s_price>-9,545</s_price><sep/><s_nm>SubTotal:</s_nm><s_price>63,636</s_price><sep/><s_nm>Discount:</s_nm><s_price>-9,545</s_price><sep/><s_nm>PB1:</s_nm><s_price>5,409</s_tax_price></s_sub_total><s_total><s_total_price>59,500</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>40,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Choco Devil</s_nm><s_cnt>4</s_cnt><s_discountprice>-9,545</s_discountprice><s_price>63,636</s_price></s_menu><s_sub_total><s_subtotal_price>63,636</s_subtotal_price><s_discount_price>-9,545</s_discount_price><s_tax_price>5,409</s_tax_price></s_sub_total><s_total><s_total_price>59,500</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>40,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.3108433734939759\n",
+            "Prediction: <s_menu><s_nm>TALAM UNGU</s_nm><s_price>19,500</s_price><sep/><s_nm>DISC ITEM</s_nm><s_price>-40.000嵗<sep/><s_nm>AMOUNT</s_nm><sep/><s_nm>-7,800</s_price><sep/><s_nm>MIKA KECIL</s_nm><s_price>0</s_price><sep/><s_nm>4.00xITEMs</s_nm><s_price>11,700</s_price><sep/><s_nm>SUBTOTAL</s_nm><s_cnt>1X</s_cnt><s_price>11,700</s_price><sep/><s_nm>TOTAL</s_nm><s_unitprice>11,700</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>8,300</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>TALAM UNGU</s_nm><s_unitprice>@6500</s_unitprice><s_cnt>3X</s_cnt><s_discountprice>-7,800</s_discountprice><s_price>19,500</s_price><sep/><s_nm>MIKA KECIL</s_nm><s_unitprice>@0</s_unitprice><s_cnt>1X</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>11,700</s_subtotal_price></s_sub_total><s_total><s_total_price>11,700</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>8,300</s_changeprice><s_menuqty_cnt>4.00xITEMs</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.4444444444444444\n",
+            "Prediction: <s_menu><s_nm>Tahu Ikan Oma Glok</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price><sep/><s_nm>Tahu Ikan Oma Glok</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price><sep/><s_nm>TOTAL</s_nm><s_price>20.000</s_price><sep/><s_nm>CASH</s_nm><s_price>20.000</s_price><sep/><s_nm>CHANGED</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price></s_menu><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Tahu Ikan Oma Giok</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.5420353982300885\n",
+            "Prediction: <s_menu><s_nm>Serbu</s_nm><s_cnt>2</s_cnt><s_price>40.000</s_price><sep/><s_nm>Choco Peanut Bread</s_nm><s_cnt>2</s_cnt><s_price>20.000</s_price><sep/><s_nm>TOTAL</s_nm><s_price>60.000</s_price></s_menu><s_total><s_total_price>60.000</s_total_price><s_cashprice>60.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Serbu 1</s_nm><s_cnt>2</s_cnt><s_price>40.000</s_price><sep/><s_nm>Choco Peanut Bread</s_nm><s_cnt>2</s_cnt><s_price>20.000</s_price></s_menu><s_total><s_total_price>60.000</s_total_price><s_cashprice>60.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.1574074074074074\n",
+            "Prediction: <s_menu><s_nm>Se'I Sapi Sambal Matah ( R )</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price><sep/><s_nm>Se'I Sapi Lada Hitam (J)</s_nm><s_cnt>1</s_cnt><s_price>35.000</s_price><sep/><s_nm>Nasi Putih</s_nm><s_cnt>2</s_cnt><sep/><s_nm>Milk Shake Coklat</s_nm><s_cnt>2</s_cnt><s_price>10.000</s_price><sep/><s_nm>Milk</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Milk</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Milk</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Subtotal</s_nm><s_cnt>1</s_cnt><sep/><s_nm>PB</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Bi.000</s_price><sep/><s_nm>10%</s_nm><s_cnt>1</s_cnt><sep/><s_nm>8.100</s_service_price><s_tax_price>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100<sep/>89.100</s_tax_price></s_sub_total><s_total><s_total_price>89.100</s_total_price><s_cashprice>89.100</s_total_price><s_cashprice>89.100</s_cashprice><s_changeprice>0</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>Se'I Sapi Sambal Matah ( R )</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price><sep/><s_nm>Se'I Sapi Lada Hitam (J)</s_nm><s_cnt>1</s_cnt><s_price>35.000</s_price><sep/><s_nm>Nasi Putih</s_nm><s_cnt>2</s_cnt><s_price>10.000</s_price><sep/><s_nm>Milk Shake Coklat</s_nm><s_cnt>1</s_cnt><s_price>16.000</s_price></s_menu><s_sub_total><s_subtotal_price>81.000</s_subtotal_price><s_tax_price>8.100</s_tax_price></s_sub_total><s_total><s_total_price>89.100</s_total_price><s_changeprice>0</s_changeprice><s_creditcardprice>89.100</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.49637305699481865\n",
+            "Prediction: <s_menu><s_nm>ES KOPI SUSU</s_nm><s_unitprice>72.000</s_unitprice><sep/><s_nm>Total</s_nm><s_price>72.000</s_price><sep/><s_nm>GoPay</s_nm><s_price>72.000</s_price><sep/><s_nm>Kembali</s_nm><s_price>72.000</s_price><sep/><s_nm>GoPay</s_nm><s_price>72.000</s_price><sep/><s_nm>Kembali</s_nm><s_price>0</s_price><sep/><s_nm>Kembali</s_nm><s_price>0</s_price><sep/><s_nm>GoPay</s_nm><s_price>72.000</s_price><sep/><s_nm>Kembali</s_nm><s_unitprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>ES KOPI SUSU</s_nm><s_cnt>4</s_cnt><s_price>72.000</s_price></s_menu><s_total><s_total_price>72.000</s_total_price><s_changeprice>0</s_changeprice><s_emoneyprice>72.000</s_emoneyprice></s_total>\n",
+            " Normed ED: 0.6114649681528662\n",
+            "Prediction: <s_menu><s_nm>MINERAL 600 ML</s_nm><s_cnt>1</s_cnt><s_price>7,727</s_price><sep/><s_nm>BULGOGI RICE R</s_nm><s_cnt>1</s_cnt><s_price>33,636</s_price><sep/><s_nm>Subtotal</s_nm><s_cnt>1</s_cnt><s_price>41,364</s_price><sep/><s_nm>Tax</s_nm><s_cnt>1</s_cnt><s_price>4,136</s_price><sep/><s_nm>Total</s_nm><s_cnt>1</s_cnt><s_price>45,500</s_price><sep/><s_nm>CASH</s_nm><s_cnt>50,000</s_total_price><s_cashprice>-4,500</s_cashprice><s_changeprice>-4,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>MINERAL 600 ML</s_nm><s_cnt>1</s_cnt><s_price>7,727</s_price><sep/><s_nm>BULGOGI RICE R</s_nm><s_cnt>1</s_cnt><s_price>33,636</s_price></s_menu><s_sub_total><s_subtotal_price>41,364</s_subtotal_price><s_tax_price>4,136</s_tax_price></s_sub_total><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>-4,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.3088235294117647\n",
+            "Prediction: <s_menu><s_nm>Arem Arem Arem</s_nm><s_unitprice>@12.000</s_unitprice><sep/><s_nm>Kroket</s_nm><s_price>24.000</s_price><sep/><s_nm>@12.000</s_unitprice><sep/><s_nm>Rp 36.000</s_unitprice><s_cnt>2x</s_cnt><s_price>Rp 3.600</s_price><sep/>Rp 39.600</s_unitprice><s_cnt>Rp 39.600</s_unitprice><s_cnt>Rp 39.600</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Arem Arem</s_nm><s_unitprice>@ 12.000</s_unitprice><s_cnt>2 x</s_cnt><s_price>24.000</s_price><sep/><s_nm>Kroket</s_nm><s_unitprice>@ 12.000</s_unitprice><s_cnt>1 x</s_cnt><s_price>12.000</s_price></s_menu><s_sub_total><s_subtotal_price>Rp 36.000</s_subtotal_price><s_tax_price>Rp 3.600</s_tax_price></s_sub_total><s_total><s_total_price>Rp 39.600</s_total_price><s_emoneyprice>Rp 39.600</s_emoneyprice></s_total>\n",
+            " Normed ED: 0.3981264637002342\n",
+            "Prediction: <s_menu><s_nm>Arem Arem Arem</s_nm><sep/><s_nm>12.000</s_unitprice><s_cnt>2</s_cnt><s_price>24.000</s_price><sep/><s_nm>Pepenero Pastel</s_nm><s_price>15.000</s_price><sep/><s_nm>Rp 54.000</s_price><sep/>Rp 5.400</s_unitprice><s_cnt>2</s_cnt><s_price>Rp 5.400</s_price><sep/>Rp 59.400</s_emoneyprice>Rp 100.000</s_emoneyprice>Rp Rp Rp 40.600</s_emoneyprice>Rp 100.000</s_emoneyprice>Rp Rp 40.600</s_emoneyprice>Rp 100.000</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Arem Arem</s_nm><s_unitprice>12.000</s_unitprice><s_cnt>2</s_cnt><s_price>24.000</s_price><sep/><s_nm>Pepenero Pastel</s_nm><s_unitprice>15.000</s_unitprice><s_cnt>2</s_cnt><s_price>30.000</s_price></s_menu><s_sub_total><s_subtotal_price>Rp 54.000</s_subtotal_price><s_tax_price>Rp 5.400</s_tax_price></s_sub_total><s_total><s_total_price>Rp 59.400</s_total_price><s_cashprice>Rp 100.000</s_cashprice><s_changeprice>Rp 40.600</s_changeprice></s_total>\n",
+            " Normed ED: 0.4043010752688172\n",
+            "Prediction: <s_menu><s_nm>TT</s_nm><s_price>20,000</s_price><sep/><s_nm>TOTAL</s_nm><s_price>20,000</s_price><sep/><s_nm>CASH</s_nm><s_price>100,000</s_price><sep/><s_nm>CHANGE</s_nm><s_price>80,000</s_price><sep/><s_nm>CASH</s_nm><s_price>100,000</s_price><sep/><s_nm>CHANGE</s_nm><s_price>80,000</s_price><sep/><s_nm>CASH</s_nm><s_unitprice>100,000</s_price><sep/><s_nm>CHANGE</s_nm><s_unitprice>80,000</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>TT</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.569377990430622\n",
+            "Prediction: <s_menu><s_nm>LEMONADE 16OZ</s_nm><s_unitprice>X</s_cnt><s_price>20.000</s_price><sep/><s_nm>X</s_nm><s_price>20.000</s_price><sep/><s_nm>SUB TOTAL</s_nm><s_price>20,000</s_price><sep/><s_nm>GRAND TOTAL</s_nm><s_price>20,000</s_price><sep/><s_nm>CASHIDR</s_nm><s_price>100,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>LEMONADE 16OZ</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_sub_total><s_subtotal_price>20,000</s_subtotal_price></s_sub_total><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80.000</s_changeprice></s_total>\n",
+            " Normed ED: 0.3767772511848341\n",
+            "Prediction: <s_menu><s_nm>beef C roll 3pcs</s_nm><s_unitprice>10,000</s_unitprice><sep/><s_nm>Kaya bred</s_nm><s_unitprice>10,000</s_unitprice><sep/><s_nm>Kaya bred</s_nm><s_unitprice>10,000</s_unitprice><sep/><s_nm>1</s_cnt><s_price>10,000</s_price><sep/><s_nm>1</s_cnt><s_price>15,000</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>2</s_cnt><s_price>25,000</s_price><sep/><s_nm>CASH</s_nm><s_cnt>1</s_cnt><s_price>100,000</s_price></s_menu><s_total><s_total_price>75,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>7</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>beef C roll 3pcs</s_nm><s_unitprice>10,000</s_unitprice><s_cnt>1</s_cnt><s_price>10,000</s_price><sep/><s_nm>kaya bred</s_nm><s_unitprice>15,000</s_unitprice><s_cnt>1</s_cnt><s_price>15,000</s_price></s_menu><s_total><s_total_price>25,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>75,000</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.4036697247706422\n",
+            "Prediction: <s_menu><s_nm>FUTAMI 17 GREEN TEA (CLAS</s_nm><s_cnt>1</s_cnt><s_price>12,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>GRAIN CROQUE MONSIEUR</s_nm><s_cnt>1</s_cnt><s_price>17,000</s_price><sep/><s_nm>GRAIN CROQUE</s_nm><s_cnt>1</s_cnt><s_price>17,000</s_price></s_menu><s_total><s_total_price>42,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>7,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>FUTAMI 17 GREEN TEA (CLAS</s_nm><s_cnt>1</s_cnt><s_price>12,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>GRAIN CROQUE MONSIEUR</s_nm><s_cnt>1</s_cnt><s_price>17,000</s_price></s_menu><s_total><s_total_price>42,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>7,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.16289592760180996\n",
+            "Prediction: <s_menu><s_nm>JAMUR</s_nm><s_cnt>2</s_cnt><s_price>10,000</s_price><sep/><s_nm>TAHU</s_nm><s_cnt>2</s_cnt><s_price>5,000</s_price><sep/><s_nm>SUBTOTAL</s_nm><s_cnt>1</s_cnt><s_price>15,000</s_price><sep/><s_nm>PB 1</s_cnt><s_price>1,500</s_price><sep/><s_nm>TOTAL</s_nm><s_price>20,000</s_price><sep/><s_nm>CASH</s_nm><s_price>3,500</s_price><sep/><s_nm>Change</s_nm><s_cnt>2</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>JAMUR</s_nm><s_cnt>2</s_cnt><s_price>10,000</s_price><sep/><s_nm>TAHU</s_nm><s_cnt>1</s_cnt><s_price>5,000</s_price></s_menu><s_sub_total><s_subtotal_price>15,000</s_subtotal_price><s_tax_price>1,500</s_tax_price></s_sub_total><s_total><s_total_price>16,500</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>3,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.39900249376558605\n",
+            "Prediction: <s_menu><s_nm>Mango Lemon Tea</s_nm><s_cnt>1</s_cnt><s_price>Rp 29,090</s_price><sep/><s_nm>Sliders Set</s_nm><s_cnt>1</s_cnt><s_price>Rp 113,636</s_price><sep/><s_nm>Chicken Vege Rice Bowl</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Rp 86,363<sep/><s_nm>Discount BCA 15%</s_nm><s_cnt>1</s_cnt><sep/><s_nm>- Rp 34,363<sep/><s_nm>Net Total: Rp 194,726<sep/>Rp 9,736</s_tax_price></s_sub_total><s_total><s_total_price>Rp 224,908</s_total_price><s_cashprice>Rp 224,908</s_cashprice><s_changeprice>Rp 224,908</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Mango Lemon Tea</s_nm><s_cnt>1</s_cnt><s_price>Rp 29,090</s_price><sep/><s_nm>Sliders Set</s_nm><s_cnt>1</s_cnt><s_price>Rp 113,636</s_price><sep/><s_nm>Chicken Vege Rice Bowl</s_nm><s_cnt>1</s_cnt><s_price>Rp 86,363</s_price><sep/><s_nm>Discount BCA 15%</s_nm><s_cnt>1</s_cnt><s_price>-Rp 34,363</s_price></s_menu><s_sub_total><s_subtotal_price>Rp 194,726</s_subtotal_price><s_service_price>Rp 9,736</s_service_price><s_tax_price>Rp 20,446</s_tax_price></s_sub_total><s_total><s_total_price>Rp 224,908</s_total_price><s_creditcardprice>Rp 224,908</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.2825719120135364\n",
+            "Prediction: <s_menu><s_nm>RedVelvet Nutella</s_nm><s_cnt>1</s_cnt><s_price>280,000</s_price><sep/><s_nm>Free Mini Candle</s_nm><s_cnt>1</s_cnt><s_price>5</s_cnt><sep/><s_nm>Large Box</s_nm><s_cnt>1</s_cnt><s_price>280,000</s_price><sep/><s_nm>SUBTOTAL</s_nm><s_cnt>1</s_cnt><s_price>280,000</s_price><sep/><s_nm>PB 1</s_cnt><s_price>28,000</s_price></s_menu><s_total><s_total_price>308,000</s_total_price><s_cashprice>308,000</s_cashprice><s_changeprice>308,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>RedVelvet Nutella</s_nm><s_cnt>1</s_cnt><s_price>280,000</s_price><s_sub><s_nm>Free Mini Candle</s_nm><s_cnt>.5</s_cnt><sep/><s_nm>Large Box</s_nm><s_cnt>1</s_cnt></s_sub></s_menu><s_sub_total><s_subtotal_price>280,000</s_subtotal_price><s_tax_price>28,000</s_tax_price></s_sub_total><s_total><s_total_price>308,000</s_total_price><s_creditcardprice>308,000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.33052631578947367\n",
+            "Prediction: <s_menu><s_nm>BUBBLE GUM</s_nm><s_cnt>1</s_cnt><s_price>18,182</s_price><sep/><s_nm>Subtotal</s_nm><s_cnt>1</s_cnt><s_price>18,182</s_price><sep/><s_nm>PAJAK 10%</s_nm><s_cnt>1</s_cnt><s_price>1,818</s_price><sep/><s_nm>Total</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>20.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>BUBBLE GUM</s_nm><s_cnt>1</s_cnt><s_price>18,182</s_price></s_menu><s_sub_total><s_subtotal_price>18,182</s_subtotal_price><s_tax_price>1,818</s_tax_price></s_sub_total><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.40931372549019607\n",
+            "Prediction: <s_menu><s_nm>PAIN AU CHOCOLATE</s_nm><s_cnt>1</s_cnt><s_price>11,000</s_price><sep/><s_nm>CHOCO CUSTARD PASTRY</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>MILK PASTRY ROLL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>REAL CHEESE INSIDE BREAD</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><sep/><s_nm>HAM CHEESE FLAT BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>1</s_cnt><s_price>100,000</s_price><sep/><s_nm>CASH</s_nm><s_cnt>1</s_cnt><sep/><s_nm>CHANGE</s_nm><s_cnt>1</s_cnt><s_price>19,500</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>PAIN AU CHOCOLATE</s_nm><s_cnt>1</s_cnt><s_price>11,000</s_price><sep/><s_nm>CHOCO CUSTARD PASTRY</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>MILK PASTRY ROLL</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>REAL CHEESE INSIDE BREAD</s_nm><s_cnt>1</s_cnt><s_price>13,500</s_price><sep/><s_nm>SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>15,000</s_price><sep/><s_nm>HAM CHEESE FLAT BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>80,500</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>19,500</s_changeprice></s_total>\n",
+            " Normed ED: 0.2878289473684211\n",
+            "Prediction: <s_menu><s_nm>Prs Sop Sui Jiao</s_nm><s_cnt>1Prs Na Kaou Udng</s_nm><s_cnt>1Prs Sio May Kpting</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_cnt><s_price>28,000</s_price><sep/><s_nm>Siomay Kmbinasi</s_nm><s_cnt>1Prs</s_cnt><sep/><s_nm>1Prs Lio Kong Kien</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1Prs</s_nm><s_cnt>1</s_cnt><s_price>23,000</s_price><sep/><s_nm>Mic Kokung Trsi</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Teh Jawar</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Teh</s_nm><s_cnt>1</s_cnt><s_price>180,000<sep/><s_nm>Service</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>Pb</s_nm><s_cnt>1</s_cnt><s_price>18,900<sep/><s_nm>Total</s_nm><s_unitprice>207,900<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>iPod<sep/>1Prs Sop Sui丁戶戶戶戶戶戶戶戶戶 PIC Sui</s_nm><sep/>1Prs Sop Sui Xiao</s_nm><sep/>1Prs Sop Sui</s_nm><sep/>1Prs Sop Sui Xiao</s_nm><sep/>1Prs Sop Sui</s_nm><sep/>1Prs Sop Sui</s_nm><sep/>1Prs Sop Sui</s_nm><sep/>1Prs Sop Sui</s_nm><sep/>1Prs Sop Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui事 PIC Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui事 PIC Sui</s_nm><sep/>1Prs Sui</s_nm><sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui事<sep/>1Prs Sui 1Prs Sui 1Prs Sui 1Prs Sui 1Prs Sui 1Prs Sui\n",
+            "    Answer: <s_menu><s_nm>Sop Sui Jiao</s_nm><s_cnt>1Prs</s_cnt><s_price>33,000</s_price><sep/><s_nm>Ha Kaou Udng</s_nm><s_cnt>1Prs</s_cnt><s_price>28,000</s_price><sep/><s_nm>Sio May Kpting</s_nm><s_cnt>1Prs</s_cnt><s_price>23,500</s_price><sep/><s_nm>Siomay Kmbinasi</s_nm><s_cnt>1Prs</s_cnt><s_price>23,000</s_price><sep/><s_nm>Leng Hong Kien</s_nm><s_cnt>1Prs</s_cnt><s_price>30,000</s_price><sep/><s_nm>Mie Trsi Kgkung</s_nm><s_cnt>1Prs</s_cnt><s_price>35,500</s_price><sep/><s_nm>Es Teh Tawar</s_nm><s_cnt>1Gls</s_cnt><s_price>7,000</s_price></s_menu><s_sub_total><s_subtotal_price>180,000</s_subtotal_price><s_service_price>9,000</s_service_price><s_tax_price>18,900</s_tax_price></s_sub_total><s_total><s_total_price>207,900</s_total_price><s_menutype_cnt>7</s_menutype_cnt><s_menuqty_cnt>7</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.826215505913272\n",
+            "Prediction: <s_menu><s_nm>NASI MERAH/PUTIH</s_nm><sep/><s_nm>5,000</s_unitprice><sep/><s_nm>5,000</s_unitprice><sep/><s_nm>5,000</s_unitprice><sep/><s_nm>4.000</s_unitprice><sep/><s_nm>KERUPUK SAMBEL</s_nm><s_price>8,000</s_price><sep/><s_nm>KERUPUK SAMBEL</s_nm><s_price>2.000</s_price><sep/><s_nm>1x2.000</s_unitprice><sep/><s_nm>AYAM</s_nm><s_price>2.000</s_price><sep/><s_nm>1x14.000</s_unitprice><sep/><s_nm>MINUMAN KEMASAN/REFILL</s_nm><s_unitprice>0</s_cnt><s_price>14.000</s_price><sep/><s_nm>KEMASAN/REFILL</s_nm><s_unitprice>6.000</s_unitprice><sep/><s_nm>Total</s_nm><s_unitprice>0</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>NASI MERAH/PUTIH</s_nm><s_unitprice>5.000</s_unitprice><s_cnt>1x</s_cnt><s_price>5.000</s_price><sep/><s_nm>SAYUR</s_nm><s_unitprice>4.000</s_unitprice><s_cnt>2x</s_cnt><s_price>8.000</s_price><sep/><s_nm>KERUPUK/SAMBEL</s_nm><s_unitprice>2.000</s_unitprice><s_cnt>1x</s_cnt><s_price>2.000</s_price><sep/><s_nm>AYAM</s_nm><s_unitprice>14.000</s_unitprice><s_cnt>1x</s_cnt><s_price>14.000</s_price><sep/><s_nm>MINUMAN KEMASAN/REFILL</s_nm><s_unitprice>6.000</s_unitprice><s_cnt>1x</s_cnt><s_price>6.000</s_price></s_menu><s_total><s_total_price>Rp. 35.000</s_total_price></s_total>\n",
+            " Normed ED: 0.39603960396039606\n",
+            "Prediction: <s_menu><s_nm>THAI ICED TEA (L)</s_nm><s_price>16,363</s_price><sep/><s_nm>16,363<sep/><s_nm>Jumlah Item</s_nm><s_price>16,363</s_price><sep/><s_nm>Sub Total</s_nm><s_price>16,363<sep/><s_nm>Pajak Resto</s_nm><s_price>1,636</s_price><sep/><s_nm>Grand Total</s_nm><s_unitprice>17,999<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>TH C Invest<sep/><sep/><sep/>THAI THAI ITE (<sep/><sep/><sep/><sep/><sep/><sep/>THAI ITEA<sep/>THAI ITEA<sep/>THAI ITEA代表 ITEA</s_nm><sep/>THAI ICED</s_nm><sep/><sep/><sep/><sep/>THAI ICED ICED ICED ICED ICED ICED ICED TEA (L)</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>THAI TEA (L)</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>THAI TEA (L)</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/>THAI TEA (L)</s_nm><sep/><sep/><sep/><sep/><sep/><sep/>THAI ICED TEA (L) TEA (L)</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363 ICED ICED ICED TEA (L) ICED TEA (L) TEA (L) TEA</s_nm><s_unitprice>16,363 ICED TEA</s_nm><s_unitprice>16,363 TEA</s_nm><s_unitprice>16,363 ICED TEA</s_nm><s_unitprice>16,363 TEA</s_nm><s_unitprice>16,363 ICED TEA</s_nm><s_unitprice>16,363 TEA</s_nm><s_unitprice>16,363 ICED ICED TEA</s_nm><s_unitprice>16,363 ITE (L) ITE (L) ITE (L) ITE (L) ITE (L) ITE (L) ITE (L) ITE) ITE (L) ITE) ITE) ITE (L) ITE) ITE) ITE (L) ITE) ITE (L) ITE) 016,363 016,363 016,363 016,363 016,363 016,363 016,363 016,363 016,363 016,363 016,363 016,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Sumlah Item</s_nm><sep/><s_nm>Sumlah Item</s_nm><sep/><s_nm>Sumlah Item</s_nm><sep/><s_nm>Sub\n",
+            "    Answer: <s_menu><s_nm>THAI ICED TEA (L)</s_nm><s_unitprice>16,363</s_unitprice><s_cnt>1</s_cnt><s_price>16.363</s_price></s_menu><s_sub_total><s_subtotal_price>16,363</s_subtotal_price><s_tax_price>1,636</s_tax_price></s_sub_total><s_total><s_total_price>17,999</s_total_price><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.9081412103746398\n",
+            "Prediction: <s_menu><s_nm>ELEPHANT READ BEAN</s_nm><s_unitprice>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>chapsal twister donnat</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>twilister</s_nm><s_cnt>1</s_cnt><s_price>10,000</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>22,000</s_price><sep/><s_nm>CASH</s_nm><s_cnt>2</s_cnt><s_price>22,000</s_price></s_menu><s_total><s_total_price>2</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>ELEPHANT READ BEAN</s_nm><s_unitprice>12,000</s_unitprice><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>chapsal twister donnut</s_nm><s_unitprice>10,000</s_unitprice><s_cnt>1</s_cnt><s_price>10,000</s_price></s_menu><s_total><s_total_price>22,000</s_total_price><s_cashprice>22,000</s_cashprice><s_changeprice>0</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.4117647058823529\n",
+            "Prediction: <s_menu><s_nm>Sabun Beras</s_nm><s_cnt>1</s_cnt><s_price>30000</s_price><sep/><s_nm>Sabun Beras</s_nm><s_cnt>1</s_cnt><s_price>30000</s_price><sep/><s_nm>30000</s_unitprice><s_cnt>1</s_cnt><s_price>30000</s_price><sep/><s_nm>Sub Total</s_nm><s_price>30000</s_price><sep/><s_nm>Discount (0 %)</s_nm><s_price>0</s_price><sep/><s_nm>Tunai</s_nm><s_price>50000</s_unitprice><s_cnt>0</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>Sabun Beras</s_nm><s_unitprice>30000</s_unitprice><s_cnt>1</s_cnt><s_price>30000</s_price></s_menu><s_sub_total><s_subtotal_price>30000</s_subtotal_price><s_discount_price>Discount(0%)</s_discount_price></s_sub_total><s_total><s_cashprice>50000</s_cashprice><s_changeprice>20000</s_changeprice></s_total>\n",
+            " Normed ED: 0.4801980198019802\n",
+            "Prediction: <s_menu><s_nm>REDBEAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>FRANKFRUT SAUSAGE ROLL</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>1</s_cnt><s_price>21,000</s_price><sep/><s_nm>CASH</s_nm><s_cnt>1</s_cnt><s_price>50,000</s_price></s_menu><s_total><s_total_price>21,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>29,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>REDBEAN BRE/D</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>FRANKFRUT S/USAGE ROLL</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price></s_menu><s_total><s_total_price>21,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>29,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.3119047619047619\n",
+            "Prediction: <s_menu><s_nm>PREMIUM TOAST PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>24,000</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>1</s_cnt><s_price>24,000</s_price><sep/><s_nm>CASH</s_nm><s_price>24,000</s_price></s_menu><s_total><s_total_price>24,000</s_total_price><s_cashprice>24,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>PREMIUM TOAST PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>24,000</s_price></s_menu><s_total><s_total_price>24,000</s_total_price><s_cashprice>24,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.3445121951219512\n",
+            "Prediction: <s_menu><s_nm>Nasi (MLY)</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price><sep/><s_nm>Subtotal</s_nm><s_price>6.000</s_price><sep/><s_nm>TOTAL</s_nm><s_price>6.000</s_price><sep/><s_nm>Go-Pay static QR</s_nm><s_price>6.000</s_price><sep/><s_nm>G.000</s_price><sep/><s_nm>G.CO</s_nm><s_price>6.000</s_price></s_menu><s_total><s_total_price>6.000</s_total_price><s_cashprice>6.000</s_cashprice><s_changeprice>QR</s_nm><s_unitprice>6.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Nasi (MLY)</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price></s_menu><s_sub_total><s_subtotal_price>6.000</s_subtotal_price></s_sub_total><s_total><s_total_price>6.000</s_total_price><s_emoneyprice>6.000</s_emoneyprice></s_total>\n",
+            " Normed ED: 0.5514223194748359\n",
+            "Prediction: <s_menu><s_nm>GRAINS PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,500</s_price><sep/><s_nm>ICED HIBISCUS LYCHEE TEA</s_nm><s_cnt>1</s_cnt><s_price>37,000</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>1</s_cnt><s_price>57,500</s_price><sep/><s_nm>GIFT50</s_nm><s_cnt>1</s_cnt><s_price>50,000</s_price><sep/><s_nm>811923270311</s_tax_price></s_sub_total><s_total><s_total_price>7,500</s_total_price><s_cashprice>5,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>GRAINS PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,500</s_price><sep/><s_nm>ICED HIBISCUS LYCHEE TEA</s_nm><s_cnt>1</s_cnt><s_price>37,000</s_price></s_menu><s_total><s_total_price>57,500</s_total_price><s_total_etc>50,000</s_total_etc><s_cashprice>7,500</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.34913793103448276\n",
+            "Prediction: <s_menu><s_nm>GRILLED BABY POTATO (R</s_nm><s_cnt>1</s_cnt><s_price>50,500</s_price><sep/><s_nm>TRUFFLE CREAM</s_nm><s_cnt>1</s_cnt><s_price>76,000</s_price><sep/><s_nm>CARBONARA</s_nm><s_cnt>1</s_cnt><s_price>70,500</s_price><sep/><s_nm>ORIGINAL BREWED TEA</s_nm><s_cnt>2</s_cnt><sep/><s_nm>SUBTTL</s_nm><s_cnt>2</s_cnt><s_price>46,000</s_price><sep/><s_nm>SUC CHG 6%</s_nm><s_cnt>1</s_cnt><s_price>14,580</s_price><sep/><s_nm>PB110%</s_nm><s_cnt>2</s_cnt><s_price>25,758</s_tax_price></s_sub_total><s_total><s_total_price>283,338</s_total_price><s_cashprice>283,338</s_cashprice><s_changeprice>5962</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>GRILLED BABY POTATO (R</s_nm><s_cnt>1</s_cnt><s_price>50,500</s_price><sep/><s_nm>TRUFFLE CREAM</s_nm><s_cnt>1</s_cnt><s_price>76,000</s_price><sep/><s_nm>CARBONARA</s_nm><s_cnt>1</s_cnt><s_price>70,500</s_price><sep/><s_nm>ORIGINAL BREWED TEA</s_nm><s_cnt>2</s_cnt><s_price>46,000</s_price></s_menu><s_sub_total><s_subtotal_price>243,000</s_subtotal_price><s_service_price>14,580</s_service_price><s_tax_price>25,758</s_tax_price></s_sub_total><s_total><s_total_price>283,338</s_total_price><s_creditcardprice>283,338<sep/>5962</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.268370607028754\n",
+            "Prediction: <s_menu><s_nm>BLACK PEPPER MEATBALL</s_nm><s_cnt>1</s_cnt><s_price>76,500</s_price><sep/><s_nm>QUARTO FORMANGGI PASTA</s_nm><s_cnt>1</s_cnt><s_price>82,500</s_price><sep/><s_nm>GREEN TEA WITH CRUMBLE</s_nm><s_cnt>1</s_cnt><sep/><s_nm>ORIGINAL BREWED TEA</s_nm><s_cnt>2</s_cnt><sep/><s_nm>SUBTTL</s_nm><s_cnt>2</s_cnt><sep/><s_nm>SVC CHG 6%</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SVC CHG 6%</s_nm><s_cnt>1</s_cnt><sep/><s_nm>ORIGINAL</s_nm><s_cnt>1</s_cnt><s_price>261,000</s_price><sep/><s_nm>SVC CHG 6%</s_nm><s_cnt>1</s_cnt><sep/><s_nm>PB110%</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SB 1</s_cnt><sep/><s_nm>SB7,666<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>BLACK P BLACK PEPPER BLACK PEPPER BLACK PEPPER BLACK PEPPER MEA 1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>BLACK PEPPER MEAリスト BLACK PEPPER MEAリスト BLACK PEPPER MEATRE 1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>BRACK PEPPER MEATRE 1</s_cnt><sep/></s_nm><s_cnt>1</s_cnt><sep/><s_nm>BRACK PEPPER MEATRE BRACK PEPPER MEATS ALLOCK PEPPER MEATS ALLOCK PEPPER MEATBALL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>BRACK PEPPER MEATBALL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>BRACK PEPPER MEATS ALLOPER MEATBALL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>QUARTO BRACK PEPPER MEATBALL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>BRACK PEPPER</s_nm><s_cnt>1</s_cnt><sep/><s_nm>QUARTO BRACK PEPPER MEATS PEPPER</s_nm><s_cnt>1</s_cnt><sep/><s_nm>BRACK PEPP ER BRACK PEPP ER WITHALL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>QUARTO GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN BRACK BRACK BRACK BRACK BRACK BRACK BRACK BRACK BRACK BRACK BRACK BRACK BRACK BRACK BRACK TEA WITH CRUNGGI PASTA WITH CRUNGGI PASTA WITH CRUNGGI PASTA WITH CRUMBLE</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><s_nm>GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN GREEN\n",
+            "    Answer: <s_menu><s_nm>BLACK PEPPER MEATBALL</s_nm><s_cnt>1</s_cnt><s_price>76,500</s_price><sep/><s_nm>QUARTO FORMANGGI PASTA</s_nm><s_cnt>1</s_cnt><s_price>82,500</s_price><sep/><s_nm>GREEN TEA WITH CRUMBLE</s_nm><s_cnt>1</s_cnt><s_price>56,000</s_price><sep/><s_nm>ORIGINAL BREWED TEA</s_nm><s_cnt>2</s_cnt><s_price>46,000</s_price></s_menu><s_sub_total><s_subtotal_price>261,000</s_subtotal_price><s_service_price>15,660</s_service_price><s_tax_price>27,666</s_tax_price></s_sub_total><s_total><s_total_price>304,326</s_total_price></s_total>\n",
+            " Normed ED: 0.8583038869257951\n",
+            "Prediction: <s_menu><s_nm>Soft Ori 3 Top</s_nm><s_cnt>1</s_cnt><s_price>17,2722</s_price><sep/><s_nm>Top Oreo</s_nm><sep/><s_nm>Top Oreo</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>Top Oreo</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>Top Banana</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>SubTotal:</s_nm><s_cnt>1</s_cnt><s_price>17,272</s_price><sep/><s_nm>PB1:</s_nm><s_cnt>1,727</s_tax_price></s_sub_total><s_total><s_total_price>18,999</s_total_price><s_cashprice>18,999</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Soft Ori 3 Top</s_nm><s_cnt>1</s_cnt><s_price>17,272</s_price><s_sub><s_nm>Top Oreo</s_nm><s_price>0</s_price><sep/><s_nm>Top Oreo</s_nm><s_price>0</s_price><sep/><s_nm>Top Banana</s_nm><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>17,272</s_subtotal_price><s_tax_price>1,727</s_tax_price></s_sub_total><s_total><s_total_price>18,999</s_total_price><s_cashprice>18,999</s_cashprice></s_total>\n",
+            " Normed ED: 0.28378378378378377\n",
+            "Prediction: <s_menu><s_nm>Ice Lemon Tea</s_nm><s_price>13,636</s_price><sep/><s_nm>Gyro Platter - Regular</s_nm><s_cnt>1</s_cnt><s_price>50,000</s_price><sep/><s_nm>Subtotal</s_nm><s_price>63,636</s_price><sep/><s_nm>PB1-TAX Tax</s_nm><s_price>6,364</s_price><sep/><s_nm>Here Total</s_nm><s_price>70,000</s_price></s_menu><s_total><s_total_price>70,000</s_total_price><s_cashprice>70,000</s_cashprice><s_changeprice>70,000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Ice Lemon Tea</s_nm><s_price>13,636</s_price><sep/><s_nm>-<sep/>Gyro Platter Regular</s_nm><s_price>50,000</s_price></s_menu><s_sub_total><s_subtotal_price>63,636</s_subtotal_price><s_tax_price>6,364</s_tax_price></s_sub_total><s_total><s_total_price>70,000</s_total_price><s_cashprice>70,000</s_cashprice></s_total>\n",
+            " Normed ED: 0.38990825688073394\n",
+            "Prediction: <s_menu><s_nm>TT</s_nm><s_price>20,000</s_price><sep/><s_nm>TOTAL</s_nm><s_price>20,000</s_price><sep/><s_nm>CASH</s_nm><s_price>100,000</s_price><sep/><s_nm>CHANGE</s_nm><s_price>-80,000</s_price><sep/><s_nm>CASH</s_nm><s_price>100,000</s_price><sep/><s_nm>CHANGE</s_nm><s_price>-80,000</s_price><sep/><s_nm>TOTAL</s_nm><s_price>20,000</s_price><sep/><s_nm>CASH</s_nm><s_price>100,000</s_price><sep/><s_nm>CHANGE</s_nm><s_price>-80,000</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>TT</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+            " Normed ED: 0.6017316017316018\n",
+            "Prediction: <s_menu><s_nm>PKT TEL OR PERK EDI C 26,000</s_unitprice><sep/><sep/><sep/><sep/><sep/><s_nm>TERONG</s_nm><s_cnt>12,000</s_price><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>P K P Kraft C P Kraft C P Kraft C P Kraft C P Kraft C P Kraft C P Kraft C P Kraft C PKT TER G PKT TER G PKT TER Gの方が TER Gの方が TER Gの方が TER G TER OKE TER OKE TER OKE TER OKE TERONG TER ONG TER ONG TER ONG TER ONG</s_nm><sep/>PKT TER ONG</s_nm><sep/>TER ONG</s_nm>TER ONG</s_nm><sep/>TER ONG</s_nm><sep/>TER ONG</s_nm><sep/>TER ONG</s_nm>TER ONG</s_nm><sep/>TER ONG</s_nm>TER ONG</s_nm><sep/>TER ONG</s_nm><sep/>TER ONG</s_nm><sep/>TER G TERONG</s_nm>TER G TERONG</s_nm>TER G PARU SBL GR TER G PARU SBL GR ARI PERK TER G PARU SBL GR ARI PERK ARI PERK ARIZ PERK ARIZ PERK ATE/AMPLA</s_nm><s_cnt>12,000</s_price><sep/>ATE TER G PARU SBL GR ARI ATE ATE/AMPLA</s_nm>ATE/AMPLA</s_nm>20,000 °C ATE/AMPLA 20,000 °C 20,000 °CAL 20,000 °CAL 20,000 °CAL 20,000 °CAL TER G PARU SBL GR 20,000 °CAL 20,000 °CAL ATE/AMPLA 20,000 °CAL 20,000 °CAL 20,000 °CAL 20,000 °CAL 20,000 °CAL 20,000 °CAL 20,000 °CAL 20,000 °CAL TER OPERKEDEL TERONG</s_nm><sep/>TER G TERONG</s_nm><sep/>TER G TERONG</s_nm><sep/>TER G PARU SBL GR 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限 限優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠優惠\n",
+            "    Answer: <s_menu><s_nm>PKT TELOR/PERKEDEL</s_nm><s_price>26,000</s_price><sep/><s_nm>TERONG</s_nm><s_price>12,000</s_price><sep/><s_nm>PARU</s_nm><s_price>23,000</s_price><sep/><s_nm>SBL GR ATI/AMPLA</s_nm><s_price>20,000</s_price><sep/><s_nm>NESTLE 330 ML</s_nm><s_price>8,000</s_price></s_menu><s_sub_total><s_subtotal_price>89,000</s_subtotal_price><s_tax_price>8,900</s_tax_price></s_sub_total><s_total><s_total_price>97,900</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>2,100</s_changeprice><s_menuqty_cnt>5.00</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.8754578754578755\n",
+            "Prediction: <s_menu><s_nm>Gojek Chicken</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>Chilli Sauce H</s_nm><s_cnt>1</s_cnt><s_price>180,00</s_price><sep/><s_nm>Gojek Chicken</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Soy Sauce F</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Gojek French</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Fries</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Sub Total</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Service</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Tax</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Discount</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Bi<sep/><s_nm>Bi<sep/><s_nm>Chicken<sep/><s_nm>Chicken<sep/><s_nm>Chicken<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/>Gojek Chicken<sep/><sep/><sep/>Gojek Chicken Quick Chicken<sep/><sep/><sep/><sep/>Gojek Chicken Quick Chicken<sep/><sep/><sep/>Gojek Chicken Quick Chicken<sep/><sep/>Gojek Chicken Quick Chicken<sep/><sep/>Gojek Chicken Quick Chicken<sep/><sep/><sep/>Gojek Chicken<sep/>Gojek Chicken<sep/>Gojek Chicken Quick Chicken<sep/>Gojek Chicken<sep/>Gojek Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>Gojek Chilli Sauce H</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>Gojek Chilli Sauce H CHI Chilli Sauce H</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/>Gojek Chilli Sauce H</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>Gojek Chilli Sauce H</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>Gojek Chilli Sauce H</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/>Gojek Chilli Sauce H</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/>Gojek Chilli Sauce H</s_nm><sep/><sep/>Gojek Chilli Sauce H CHI Chilli Sauce H CHI Chilli Sauce H</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/>Gojek Chilli Cajek Chilli Cajek Chilli Cajek Chilli Cajek Chilli Cajek Chilli Cajek Chilli Cajek Chilli Cajek Chilli Cajek Chilli Cajek Chilli Cajek Chilli Cajek Chicken CHI Gojek Chicken CHI Gojek Chicken CHI Gojek Chicken CHI Chicken CHI Chicken CHI Síochán<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>Gojek Chilli Sauce f CHI Gojek Chilli Sauce f CHI Gojek Chilli Sauce f CHI Suce f\n",
+            "    Answer: <s_menu><s_nm>Gojek Chicken Chilli Sauce H</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>Gojek Chicken Soy Sauce F</s_nm><s_cnt>1</s_cnt><s_price>180,000</s_price><sep/><s_nm>Gojek French Fries</s_nm><s_cnt>1</s_cnt><s_price>70,000</s_price></s_menu><s_sub_total><s_subtotal_price>345,000</s_subtotal_price><s_discount_price>0</s_discount_price><s_service_price>0</s_service_price><s_tax_price>34,500</s_tax_price></s_sub_total><s_total><s_total_price>379,500</s_total_price></s_total>\n",
+            " Normed ED: 0.880388978930308\n",
+            "Prediction: <s_menu><s_nm>SOGOGI JAPCHAE</s_nm><s_cnt>1</s_cnt><s_price>150,000</s_price><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>label<sep/>CREAM TEOK PO KI PO KI PO KI KI 1</s_cnt><sep/>CREA丁 以來,丁 CHEESE PO KI</s_nm>CHEM CHEESE</s_nm><sep/><sep/><sep/><sep/><sep/>CREAM C風 CHEM C風 CHEM C風 CHEM CREAM TEOK PO KI C風 ONE C風 ONE C風 ONE C風 ONE C風 ONE C風 ONE C風 ONE ONEOK PO KI PO KI</s_nm><sep/></s_nm><sep/><sep/>МЕНТ МЕНТ МЕНТ МЕНТ МЕНТ МЕНТ МЕНТ МЕНТ МЕНТ МЕНТ МЕНТ МЕНТ CHEAM TEOK PO KI</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>0</s_cnt><sep/>0</s_cnt><sep/>0</s_cnt><sep/>0</s_cnt><sep/>0嵗 CHEAM TEOK PO KI EK KEUN GI KEUN GI KEUN GI KEUN GI KEUN GI KEUN GI) KIP CREAM KIP CREAM KEUN GI KEUN GI) GYE CREAM CREAM KEUN GI) GYE CREAM KEUN GI) GYE CREAM KEUN GI) GYE CREAM KEUN GI) GYE CREAM KEUN G YE C E SUNDUB PO KI PO KI PO KI EK PO KI EK SUNDUB PO KI EK SUNDUB PO KI EK SUNDUB C E G E G E GUE PO K SUNDUB SUNDUB C ICE C ICE COFFE MIX ICE COFFE MIX ICE COFFE MIX ICE COFFE MIX ICE COFFE MIX ICE COFFE MIX BLACK COFFE MIX BLACK COFFE MIX BLACK COFFE MIX BLACK COFFE MIX BLACK COFFE MIX BLACK COFFE MIX BLACK COFFE MIX ICE BLACK COFFE MIX BLACK COFFE MIX ICE BLACK COFFE MIX ICE BLACK COFFE MIX ICE BLACK COFFE MIX ICE ICE BLACK COFFEE COFFEE COFFEE MIX BLACK COFFEE COFFEE MIX BLACK COFFEE COFFEE COFFEE MIX BLACK COFFEE COFFEE CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES CHEES\n",
+            "    Answer: <s_menu><s_nm>SOGOGI JAPCHAE</s_nm><s_cnt>1</s_cnt><s_price>150,000</s_price><sep/><s_nm>GONG GIBAB</s_nm><s_cnt>7</s_cnt><s_price>105,000</s_price><sep/><s_nm>CHULPAN CHEESE DAK GALBI</s_nm><s_cnt>1</s_cnt><s_price>230,000</s_price><sep/><s_nm>CREAM TEOK PO KI</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>EL KEUN HWANGTAE</s_nm><s_cnt>1</s_cnt><s_price>120,000</s_price><sep/><s_nm>SUNDUBU(TUKBEGI) CHAM KKOT SAL</s_nm><s_cnt>2</s_cnt><s_price>620,000</s_price><sep/><s_nm>U SAM GYEOP</s_nm><s_cnt>2</s_cnt><s_price>290,000</s_price><sep/><s_nm>U SEOL</s_nm><s_cnt>2</s_cnt><s_price>390,000</s_price><sep/><s_nm>U SAM GYEOP</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>ICE COFFE MIX</s_nm><s_cnt>3</s_cnt><s_price>0</s_price><sep/><s_nm>ICE BLACK COFFE</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>2,000,000</s_subtotal_price><s_discount_price>0</s_discount_price><s_service_price>140,000</s_service_price><s_tax_price>212,460</s_tax_price></s_sub_total><s_total><s_total_price>2,352,460</s_total_price><s_changeprice>0</s_changeprice><s_creditcardprice>2,352,460</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.835204081632653\n",
+            "Prediction: <s_menu><s_nm>STIX CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><s_nm>CINNAMON SUGAR</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>CINNAMON SUGAR</s_nm><s_cnt>1</s_cnt><sep/><s_nm>17,000</s_unitprice><sep/><s_nm>TRIPPLE CHEESE</s_nm><s_cnt>1</s_cnt><sep/><s_nm>TRIPPLE</s_nm><s_cnt>1</s_cnt><s_price>17,000</s_price><sep/><s_nm>17,000</s_price><sep/><s_nm>CHEESE</s_nm><s_cnt>1</s_cnt><sep/><s_nm>17,000</s_unitprice><sep/><s_nm>17,000<sep/><s_nm>SUB TOTAL 5,000</s_unitprice><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>STIX CINNAMON SUBIK</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>STIX CINNAMON SUBT ONL SUBT OTAL CINNAMON SUBT OTAL CINNAMON SUGAR</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>STIX CINNAMON</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>STIX CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>STIX CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>STIX CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/>CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CINNAMON</s_nm><sep/><sep/>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><sep/><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><sep/><sep/><sep/>CINNAMON</s_nm><s_unitprice>CINNAMON</s_nm><sep/><sep/><sep/><sep/><sep/><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON SUGAR</s_nm><sep/>CINNAMON</s_nm><sep/>CINNAMON SUGAR</s_nm><sep/>CINNAMON SUGAR</s_nm><sep/>TRY TRY TRY CINNAMON SUGAR</s_nm><sep/>CINNAMON SUGAR</s_nm><sep/>TRY CINNA\n",
+            "    Answer: <s_menu><s_nm>STIX CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>CINNAMON SUGAR</s_nm><s_unitprice>17,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_price><sep/><s_nm>TRIPPLE CHEESE</s_nm><s_unitprice>17,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_price></s_menu><s_sub_total><s_subtotal_price>53,000</s_subtotal_price></s_sub_total><s_total><s_total_price>53,000</s_total_price><s_changeprice>0</s_changeprice><s_creditcardprice>53,000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.8720641061066593\n",
+            "Prediction: <s_menu><s_nm>ROTI UNYIL</s_nm><s_unitprice>170</s_unitprice><s_cnt>1</s_cnt><s_price>272.000</s_price><sep/><s_nm>PAPER BAG BESAR</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price><sep/><s_nm>Total</s_nm><s_cnt>1</s_cnt><s_price>278.000</s_price><sep/><s_nm>Cash</s_nm><s_cnt>1</s_cnt><s_price>300.000</s_price></s_menu><s_total><s_total_price>22.000</s_total_price><s_cashprice>171</s_cashprice><s_changeprice>Qty.</s_nm><s_cnt>1</s_cnt><s_price>22.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>ROTI UNYIL</s_nm><s_cnt>170</s_cnt><s_price>272.000</s_price><sep/><s_nm>PAPER BAG BESAR</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price></s_menu><s_total><s_total_price>278.000</s_total_price><s_cashprice>300.000</s_cashprice><s_changeprice>22.000</s_changeprice><s_menuqty_cnt>171</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.43907563025210083\n",
+            "Prediction: <s_menu><s_nm>THAI ICED TEA (L)</s_nm><s_price>16,363</s_price><sep/><s_nm>16,363<sep/><s_nm>Jumlah Item</s_nm><s_price>16,363</s_price><sep/><s_nm>Sub Total</s_nm><s_price>16,363<sep/><s_nm>Pajak Resto</s_nm><s_price>1,636</s_price><sep/><s_nm>Grand Total</s_nm><s_unitprice>17,999<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>TH C Invest<sep/><sep/><sep/>THAI THAI ITE (<sep/><sep/><sep/><sep/><sep/><sep/>THAI ITEA<sep/>THAI ITEA<sep/>THAI ITEA代表 ITEA</s_nm><sep/>THAI ICED</s_nm><sep/><sep/><sep/><sep/>THAI ICED ICED ICED ICED ICED ICED ICED TEA (L)</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>THAI TEA (L)</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>THAI TEA (L)</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/>THAI TEA (L)</s_nm><sep/><sep/><sep/><sep/><sep/><sep/>THAI TEA (L) ICED TEA (L)</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363</s_nm><s_unitprice>16,363 ICED ICED ICED TEA (L) ICED TEA (L) TEA (L) TEA</s_nm><s_unitprice>16,363 ICED TEA</s_nm><s_unitprice>16,363 TEA</s_nm><s_unitprice>16,363 ICED TEA</s_nm><s_unitprice>16,363 TEA</s_nm><s_unitprice>16,363 ICED TEA</s_nm><s_unitprice>16,363 TEA</s_nm><s_unitprice>16,363 ICED ICED TEA</s_nm><s_unitprice>16,363 ITE (L) ITE (L) ITE (L) ITE (L) ITE (L) ITE (L) ITE (L) ITE) ITE (L) ITE) ITE) ITE) ITE (L) ITE) ITE (L) ITE) ITE) ITE) 016,363 016,363 016,363 016,363 016,363 016,363 016,363 016,363 016,363 016,363 016,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><sep/><sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>16,363<sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Jumlah Item</s_nm><sep/><s_nm>Sumlah Item</s_nm><sep/><s_nm>Sumlah Item</s_nm><sep/><s_nm>Sumlah Item</s_nm><sep/><s_nm>Sumlah Item</s_nm><sep/><s_nm>\n",
+            "    Answer: <s_menu><s_nm>THAI ICED TEA (L)</s_nm><s_unitprice>16,363</s_unitprice><s_cnt>1</s_cnt><s_price>16.363</s_price></s_menu><s_sub_total><s_subtotal_price>16.363</s_subtotal_price><s_tax_price>1,636</s_tax_price></s_sub_total><s_total><s_total_price>17,999</s_total_price><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.9094151212553495\n",
+            "Prediction: <s_menu><s_nm>AOP Seafood</s_nm><s_cnt>1</s_cnt><s_price>85,000</s_price><sep/><s_nm>Omurice Katsu Curry</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>Earl Gray Tea</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Hot Tea</s_nm><s_cnt>1</s_cnt><sep/><s_nm>Hot Tea</s_nm><s_cnt>1</s_cnt><s_price>35,000</s_price><sep/><s_nm>Hot Tea</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SUBTOTAL</s_nm><s_cnt>1</s_cnt><s_price>240,00</s_price><sep/><s_nm>Service</s_nm><s_cnt>1</s_cnt><s_price>21,600</s_price></s_menu><s_sub_total><s_subtotal_price>28,7,760<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>AOP Seafood</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/>AOP</s_nm><s_cnt>\n",
+            "    Answer: <s_menu><s_nm>AOP Seafood</s_nm><s_cnt>1</s_cnt><s_price>85,000</s_price><sep/><s_nm>Omurice Katsu Curry</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>Earl Gray Tea</s_nm><s_cnt>1</s_cnt><s_price>35,000</s_price><sep/><s_nm>Hot Tea</s_nm><s_cnt>1</s_cnt><s_price>25,000</s_price></s_menu><s_sub_total><s_subtotal_price>240,000</s_subtotal_price><s_service_price>21,600</s_service_price><s_tax_price>26,160</s_tax_price></s_sub_total><s_total><s_total_price>287,760</s_total_price></s_total>\n",
+            " Normed ED: 0.8896120150187735\n",
+            "Prediction: <s_menu><s_nm>MARBLE CASTELA</s_nm><s_unitprice>22,000</s_unitprice><sep/><s_nm>22,000</s_unitprice><s_cnt>1</s_cnt><s_price>22,000</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>1</s_cnt><s_price>22,000</s_price><sep/><s_nm>CASH</s_nm><s_cnt>1</s_cnt><s_price>22,000</s_price></s_menu><s_total><s_total_price>22,000</s_total_price><s_cashprice>0</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>MARBLE CASTELA</s_nm><s_unitprice>22,000</s_unitprice><s_cnt>1</s_cnt><s_price>22,000</s_price></s_menu><s_total><s_total_price>22,000</s_total_price><s_cashprice>22,000</s_cashprice><s_changeprice>0</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.44556962025316454\n",
+            "Prediction: <s_menu><s_nm>Seaweed Chicken</s_nm><s_cnt>1</s_cnt><s_price>42,000</s_price><sep/><s_nm>Seaweed Chicken</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>- Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>ITEMS:1</s_nm><s_cnt>1</s_cnt><s_price>42,000</s_price><sep/><s_nm>Total</s_nm><s_cnt>1</s_cnt><s_price>42,000</s_price><sep/><s_nm>Cash 50,000</s_nm><s_cnt>1</s_cnt><s_price>8,000</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Seaweed Chicken</s_nm><s_cnt>1</s_cnt><s_price>42,000</s_price><s_sub><s_nm>- Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>42,000</s_subtotal_price></s_sub_total><s_total><s_total_price>42,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>8,000</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.4485981308411215\n",
+            "Prediction: <s_menu><s_nm>SB 1 OR</s_nm><s_cnt>1</s_cnt><s_price>28,636</s_price><sep/><s_nm>Chokocha Flt</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price><sep/><s_nm>Bbq Bento</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price><sep/><s_nm>Sub Total</s_nm><s_cnt>1</s_cnt><s_price>55,908</s_price><sep/><s_nm>P.Rest 10</s_nm><s_cnt>1</s_cnt><s_price>5,592</s_price></s_menu><s_sub_total><s_subtotal_price>61,500</s_total_price><s_cashprice>70,000</s_cashprice><s_changeprice>8,500</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>SB 1 OR</s_nm><s_cnt>1</s_cnt><s_price>28,636</s_price><sep/><s_nm>Chokocha Flt</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price><sep/><s_nm>Bbq Bento</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>55,908</s_subtotal_price><s_tax_price>5,592</s_tax_price></s_sub_total><s_total><s_total_price>61,500</s_total_price><s_cashprice>70,000</s_cashprice><s_changeprice>8,500</s_changeprice><s_menuqty_cnt>3</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.25614754098360654\n",
+            "Prediction: <s_menu><s_nm>52.000</s_unitprice><sep/><s_nm>Nasi Campur Bali</s_nm><sep/><s_nm>1x</s_cnt><s_price>52.000</s_price><sep/><s_nm>Nasi Campur Bali</s_nm><sep/><s_nm>1x 22.000</s_unitprice><sep/><s_nm>Lemon</s_nm><s_price>22.000</s_price><sep/><s_nm>SubTTL</s_nm><s_price>74.000</s_price><sep/><s_nm>TAX</s_nm><s_price>7.400</s_price></s_menu><s_total><s_total_price>81-400</s_total_price><s_cashprice>81-400</s_cashprice><s_changeprice>81.400</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Nasi CampurBali</s_nm><s_unitprice>52.000</s_unitprice><s_cnt>1x</s_cnt><s_price>52.000</s_price><sep/><s_nm>Lemon</s_nm><s_unitprice>22.000</s_unitprice><s_cnt>1x</s_cnt><s_price>22.000</s_price></s_menu><s_sub_total><s_subtotal_price>74.000</s_subtotal_price><s_tax_price>7.400</s_tax_price></s_sub_total><s_total><s_cashprice>81.400</s_cashprice></s_total>\n",
+            " Normed ED: 0.4592274678111588\n",
+            "Prediction: <s_menu><s_nm>CHOCOLATE ECLAIRY</s_nm><s_cnt>2</s_cnt><s_price>26,000</s_price><sep/><s_nm>TOTAL</s_nm><s_price>26,000</s_price><sep/><s_nm>CASH</s_nm><s_price>26,000</s_price><sep/><s_nm>CHANGE</s_nm><s_price>0</s_price><sep/><s_nm>CASH</s_nm><s_price>26,000</s_price><sep/><s_nm>CHANGE</s_nm><s_price>0</s_price><sep/><s_nm>TOTAL</s_nm><s_price>26,000</s_price><sep/><s_nm>CASH</s_nm><s_price>26,000</s_price><sep/><s_nm>CHANGE</s_nm><s_unitprice>26,000<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE CHANGE CHANGE G<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE CHANGE CHANGE CHANGE G cais<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE CHANGE CHANGE CHANGE G cais nacionais<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE</s_nm>2,000,000</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE</s_nm>2,000,000</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE</s_nm>2,000,000 CHANGE</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE ECLAIR</s_nm><sep/><sep/><sep/><sep/>CHANGE E CHANGE ECLAIR</s_nm>20,000</s_price><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE E CHANGE E CHANGE E CHANGE E CHANGE E CHANGE E CHANGE E CHANGE</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CLASH OCOOLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECLATE ECL Across Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen Citroen निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम निगम<sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>CHANGE 6,000</s_price><sep/>CHANGE BLUE E CHANGE 6,000</s_price><sep/>6,000</s_price><sep/>6,000</s_price><sep/>6,000</s_price><sep/>6,000</s_price><sep/>6,000</s_price><sep/>6,000</s_price><sep/>6,000</s_price><sep/>6,000</s_price><sep/>6,000</s_price><sep/>6,000</s_price><sep/>6,000<sep/>6,000<sep/>6,000<sep/>6,000<sep/>6,000<sep/>6,000\n",
+            "    Answer: <s_menu><s_nm>CHOCOLATE ECLAIR</s_nm><s_cnt>2</s_cnt><s_price>26,000</s_price></s_menu><s_total><s_total_price>26,000</s_total_price><s_cashprice>26,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.9509536784741145\n",
+            "Prediction: <s_menu><s_nm>118 Round Wigyu (1gr)</s_nm><s_cnt>1</s_cnt><s_price>47.200</s_price><sep/><s_nm>Wagyu Rice Box</s_nm><s_cnt>1</s_cnt><s_price>10,000</s_price><sep/><s_nm>Subtotal</s_nm><s_cnt>1</s_cnt><s_price>57.200</s_price><sep/><s_nm>TOTAL</s_nm><s_cnt>1</s_cnt><s_price>57.200</s_price><sep/><s_nm>BCA</s_nm><s_cnt>1</s_cnt><s_price>57.200</s_price></s_menu><s_total><s_total_price>57.200</s_total_price><s_cashprice>57.200</s_cashprice><s_changeprice>BCA</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Round Wagyu (1gr)</s_nm><s_cnt>118</s_cnt><s_price>47.200</s_price><sep/><s_nm>Wagyu Rice Box</s_nm><s_cnt>1</s_cnt><s_price>10.000</s_price></s_menu><s_sub_total><s_subtotal_price>57.200</s_subtotal_price></s_sub_total><s_total><s_total_price>57.200</s_total_price><s_creditcardprice>57.200</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.41649484536082476\n",
+            "Prediction: <s_menu><s_nm>KENTHIR 2</s_nm><s_price>42.000</s_price><sep/><s_nm>KOL GORENG</s_nm><s_price>6.000</s_price><sep/><s_nm>TEH MANIS</s_nm><s_price>8.000</s_price><sep/><s_nm>Subtotal</s_nm><s_price>56.000</s_price><sep/><s_nm>Total</s_nm><s_price>56.000</s_price><sep/><s_nm>CASH</s_nm><s_price>56.000</s_price><sep/><s_nm>Kembalan</s_nm><s_unitprice>56.000</s_price><sep/><s_nm>Kembalan</s_nm><s_unitprice>0</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>KENTHIR 2</s_nm><s_cnt>2</s_cnt><s_price>42.000</s_price><sep/><s_nm>KOL GORENG</s_nm><s_cnt>2</s_cnt><s_price>6.000</s_price><sep/><s_nm>TEH MANIS</s_nm><s_cnt>2</s_cnt><s_price>8.000</s_price></s_menu><s_sub_total><s_subtotal_price>56.000</s_subtotal_price></s_sub_total><s_total><s_total_price>56.000</s_total_price><s_cashprice>56.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.4652777777777778\n",
+            "Prediction: <s_menu><s_nm>Large</s_nm><s_cnt>1</s_cnt><s_price>11.000</s_price><sep/><s_nm>*Rhum</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>Pastry Keju</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price><sep/><s_nm>*Plastik KCL</s_nm><s_cnt>1</s_cnt><s_price>0</s_price><sep/><s_nm>Total</s_nm><s_cnt>1</s_cnt><s_price>31.000</s_price><sep/><s_nm>Bayar</s_nm><s_cnt>1</s_cnt><s_price>40.000</s_price></s_menu><s_sub_total><s_subtotal_price>9.000</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Large 1</s_nm><s_cnt>1</s_cnt><s_price>11.000</s_price><s_sub><s_nm>*Rhum</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub><sep/><s_nm>Pastry Keju</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price><s_sub><s_nm>*Plastik kcl</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_total><s_total_price>31.000</s_total_price><s_cashprice>40.000</s_cashprice><s_changeprice>9.000</s_changeprice><s_menuqty_cnt>4</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.296137339055794\n",
+            "Prediction: <s_menu><s_nm>4003-Blueberry Fuji</s_nm><s_unitprice>40.000</s_unitprice><sep/><s_nm>6001-Plastic Bag Small</s_nm><s_unitprice>0</s_unitprice><sep/><s_nm>6001-Plastic Bag Small</s_nm><s_unitprice>0</s_unitprice><sep/><s_nm>Total Item;</s_nm><s_price>0</s_price><sep/><s_nm>Cash</s_nm><s_price>0</s_price><sep/><s_nm>Cash</s_nm><s_price>0</s_price><sep/><s_nm>Tendered:</s_nm><s_price>50.000</s_price><sep/><s_nm>Change:</s_menuqty_cnt></s_total>\n",
+            "    Answer: <s_menu><s_nm>4003-Blueberry Fuji</s_nm><s_unitprice>40.000</s_unitprice><s_cnt>x1</s_cnt><s_price>40.000</s_price><sep/><s_nm>6001-Plastic Bag Small</s_nm><s_unitprice>0</s_unitprice><s_cnt>x1</s_cnt><s_price>0</s_price></s_menu><s_total><s_total_price>40.000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>10.000</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+            " Normed ED: 0.3752808988764045\n",
+            "Prediction: <s_menu><s_nm>Cha Keaw L... x2</s_nm><s_price>60.000</s_price><sep/><s_nm>Cha Keaw L... x2</s_nm><s_price>60.000</s_price><sep/><s_nm>BCA PAY... (100%)</s_nm><s_price>60.000</s_price><sep/><s_nm>Total</s_nm><s_price>60.000</s_price><sep/><s_nm>EDC</s_nm><s_price>60.000</s_price><sep/><s_nm>B C<sep/><s_nm>BCA</s_nm><s_unitprice>(100%)</s_nm><s_unitprice>60.000</s_price><sep/><s_nm>Total</s_nm><s_unitprice>60.000</s_unitprice><s_cnt>60.000</s_unitprice><s_cnt>60.000</s_emoneyprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Cha Keaw L...</s_nm><s_cnt>x2</s_cnt><s_price>60.000</s_price><sep/><s_nm>Cha Keaw L...</s_nm><s_cnt>x2</s_cnt><s_discountprice>60.000)</s_discountprice><s_price>60.000</s_price></s_menu><s_total><s_total_price>60.000</s_total_price><s_creditcardprice>60.000</s_creditcardprice></s_total>\n",
+            " Normed ED: 0.5323886639676113\n",
+            "Prediction: <s_menu><s_nm>Thai Iced T..x]</s_nm><s_price>20.000</s_price><sep/><s_nm>Subtotal</s_nm><s_price>20.000</s_price><sep/><s_nm>Total</s_nm><s_price>20.000</s_price><sep/><s_nm>Cash</s_nm><s_price>20.000</s_price><sep/><s_nm>Change</s_nm><s_price>20.000</s_price></s_menu><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>20.000</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Thai Iced T. .x1</s_nm><s_price>20.000</s_price></s_menu><s_sub_total><s_subtotal_price>20.000</s_subtotal_price></s_sub_total><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.41012658227848103\n",
+            "Prediction: <s_menu><s_nm>SEAFOOD MARINARA</s_nm><s_cnt>1</s_cnt><s_price>85,000</s_price><sep/><s_nm>CREAMY MARINARA SALMON</s_nm><s_cnt>1</s_cnt><s_price>85,500</s_price><sep/><s_nm>LYCHEE ICE TEA</s_nm><s_cnt>2</s_cnt><s_price>77,000</s_price><sep/><s_nm>SUBTTL</s_nm><s_cnt>1</s_cnt><s_price>247,500</s_price><sep/><s_nm>SVC CHG 6%</s_nm><s_cnt>1</s_cnt><s_price>14,850</s_price><sep/><s_nm>PBl 10%</s_nm><s_cnt>1</s_cnt><s_price>26,235</s_price><sep/><s_nm>LYCHEE ICE TEA</s_nm><s_cnt>2</s_cnt><sep/><s_nm>SUBTTL</s_nm><s_cnt>1</s_cnt><sep/><s_nm>SVC CHG 6%</s_nm><s_cnt>1</s_cnt><sep/><s_nm>CHG</s_nm><s_cnt>1</s_cnt><sep/><s_nm>PBl 10%</s_nm><s_cnt>1</s_cnt><sep/><s_nm>PBl 10%</s_nm><s_cnt>1</s_cnt><sep/><s_nm>ICE TEA</s_nm><s_cnt>1</s_cnt><sep/><s_nm>LYCHEE ICE TEA</s_nm><s_cnt>2</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>| SEAFOOD MARINARAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績績<s_nm>SEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><s_nm>SEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><s_nm>SEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><s_nm>SEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><s_nm>SEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><s_nm>SEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>PICNICHIY MARINARA</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>PICNICHINESSEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>PICNICHINESSEAFOOD MARINARA</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><s_nm>SEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>PICNICHINESSEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>PICNICHINESSEAFOOD MARINARA</s_nm><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>PICNICHINESSEAFOOD MARINARA</s_nm><s_cnt>1</s_cnt><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/><sep/>\n",
+            "    Answer: <s_menu><s_nm>SEAFOOD MARINARA</s_nm><s_cnt>1</s_cnt><s_price>85,000</s_price><sep/><s_nm>CREAMY MARINARA SALMON</s_nm><s_cnt>1</s_cnt><s_price>85.500</s_price><sep/><s_nm>LYCHEE ICE TEA</s_nm><s_cnt>2</s_cnt><s_price>77,000</s_price></s_menu><s_sub_total><s_subtotal_price>247,500</s_subtotal_price><s_service_price>14,850</s_service_price><s_tax_price>26,235</s_tax_price></s_sub_total><s_total><s_total_price>288,585</s_total_price></s_total>\n",
+            " Normed ED: 0.8889568675435913\n",
+            "Prediction: <s_menu><s_nm>Viet Milk Coffee</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price><sep/><s_nm>+Hot</s_nm><s_price>+M</s_nm><s_price>25.000</s_price></s_menu><s_total><s_total_price>25,000</s_total_price><s_cashprice>25.000</s_cashprice><s_changeprice>Rp 0</s_changeprice></s_total>\n",
+            "    Answer: <s_menu><s_nm>Viet Milk Coffee</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price><s_sub><s_nm>+Hot</s_nm><sep/><s_nm>+M</s_nm></s_sub></s_menu><s_sub_total><s_subtotal_price>25.000</s_subtotal_price></s_sub_total><s_total><s_total_price>25.000</s_total_price><s_cashprice>25.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+            " Normed ED: 0.22054380664652568\n"
+          ]
+        }
+      ],
+      "source": [
+        "from pytorch_lightning.loggers import WandbLogger\n",
+        "from pytorch_lightning.callbacks import Callback, EarlyStopping\n",
+        "\n",
+        "wandb_logger = WandbLogger(project=\"Donut\", name=\"demo-run-cord\")\n",
+        "\n",
+        "class PushToHubCallback(Callback):\n",
+        "    def on_train_epoch_end(self, trainer, pl_module):\n",
+        "        print(f\"Pushing model to the hub, epoch {trainer.current_epoch}\")\n",
+        "        pl_module.model.push_to_hub(\"nielsr/donut-demo\",\n",
+        "                                    commit_message=f\"Training in progress, epoch {trainer.current_epoch}\")\n",
+        "\n",
+        "    def on_train_end(self, trainer, pl_module):\n",
+        "        print(f\"Pushing model to the hub after training\")\n",
+        "        pl_module.processor.push_to_hub(\"nielsr/donut-demo\",\n",
+        "                                    commit_message=f\"Training done\")\n",
+        "        pl_module.model.push_to_hub(\"nielsr/donut-demo\",\n",
+        "                                    commit_message=f\"Training done\")\n",
+        "\n",
+        "early_stop_callback = EarlyStopping(monitor=\"val_edit_distance\", patience=3, verbose=False, mode=\"min\")\n",
+        "\n",
+        "trainer = pl.Trainer(\n",
+        "        accelerator=\"gpu\",\n",
+        "        devices=1,\n",
+        "        max_epochs=config.get(\"max_epochs\"),\n",
+        "        val_check_interval=config.get(\"val_check_interval\"),\n",
+        "        check_val_every_n_epoch=config.get(\"check_val_every_n_epoch\"),\n",
+        "        gradient_clip_val=config.get(\"gradient_clip_val\"),\n",
+        "        precision=16, # we'll use mixed precision\n",
+        "        num_sanity_val_steps=0,\n",
+        "        # logger=wandb_logger,\n",
+        "        callbacks=[early_stop_callback],\n",
+        ")\n",
+        "\n",
+        "trainer.fit(model_module)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "LjDHXmhFprFw"
+      },
+      "source": [
+        "## Evaluate\n",
+        "\n",
+        "After training, we can evaluate the model on the test set.\n",
+        "\n",
+        "As we pushed the model to the hub, we can very easily load it back again using the `from_pretrained` method. You can see in the [repo](https://huggingface.co/nielsr/donut-demo/tree/main) that we have the following files:\n",
+        "\n",
+        "![Screenshot 2022-08-16 at 11.05.59.png](data:image/png;base64,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)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "NpHF6EdN6WLr"
+      },
+      "source": [
+        "Note that you can also easily refer to a specific commit in the `from_pretrained` method using the [`revision`](https://huggingface.co/docs/transformers/v4.21.1/en/main_classes/model#transformers.PreTrainedModel.from_pretrained.revision) argument, or use the private hub in case you'd like to keep your models private and only shared with certain colleagues for instance.\n",
+        "\n",
+        "Here we're just loading from the main branch, which means the latest commit."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 396,
+          "referenced_widgets": [
+            "da517c560a174ed3b3a0d342ab9531d4",
+            "0d29cb058287441397849858958eecc5",
+            "971fb37793b04b02916266e0606a8cd3",
+            "f397c359a4844fe0b43cbd55f7e45e2c",
+            "5be79748747e48dc9557e635185b09b7",
+            "5cf9cf4d06af477aaadf2c2eafb21a0f",
+            "acb18d163a98436abc6a34c80d0b9875",
+            "9e5391e58b654a54af53ca6b156d4027",
+            "a772a8f8485b4cbc954363c5d25a1355",
+            "c8d62278ed494aa1948d4ddac0b5e94c",
+            "9ef9d3b7c4e141c99299d21e270347af",
+            "c5810b986d064e93ac00ff911d3d09de",
+            "0d5904889d6246e4b0bd8223d9ce79ab",
+            "09e57cfef8d04198b07337e6adfd3cfd",
+            "9460488365d343e887fb88aafc4c434b",
+            "8ad84d92e3f2470084c072e64a46cfb3",
+            "8b4f59bf71c64c2293a9e089b963b914",
+            "7372f1fa693345ad8f26f0148b2f527b",
+            "3b5d54289850421e821f88fc5f0c0421",
+            "bcaced45f306473887ab7c07df871481",
+            "4cacd92cb1f04dcea344f93e816d6244",
+            "fd4d064de57d469c977318add3069303",
+            "5d99e7c78ae54a2fa6824cfe36498ab4",
+            "6eec510e0a3844dfb7c7bcb3a6b9d910",
+            "dcbf40b9f3d04a29abb5b82cc4f4f43a",
+            "03a5186fafe7424c896a5c8f4b356098",
+            "0c9bb2443ecf460a876558b547c3b97f",
+            "e797e849c5e0443e84af5c12061589d4",
+            "422523d56ec74035b0a55b9c97d1ed19",
+            "acfeebabb13647ddbbe4372e192b235a",
+            "b2f81adfc7624d0ebec30a6f49d3b0d3",
+            "f1a2bee7a7dc408087833912c951119d",
+            "8eef683c23a14e9ca9cc8e260a8d25aa",
+            "314069aa673f41f9abd2c6d2b634a64c",
+            "7df7c889e4794145ba5b20177df36189",
+            "f16c7f25616a478ab6ba69ce88a69724",
+            "e9b2a001c8dc4591b00a21893c56dceb",
+            "96b45a24defe461998123ec31aba1d97",
+            "f387bdb0ba094db2892ed92e786886f6",
+            "1510960e07b742c4b1d838b2d533439b",
+            "bcb3bc46a920467d8441c8fe2c0081f7",
+            "212fc0393d3a4ea9a76571c9b636ae20",
+            "a9ed7db85a364e6384f84f216080d24a",
+            "98c6ca051cde41cf806b1b8bd9caf6c9",
+            "183c1ce81c8544719ce85a79cf44f9e9",
+            "538e66a6277b478db47627b3f38b7da0",
+            "7de626274586484c966e3fcd322559af",
+            "07a8d73caf1741d78f637c5093884834",
+            "049b89f7db7b4b278b2b266771a22ef1",
+            "53f439b9ac714080972b77d4ce2e15ed",
+            "8d98ed226dd1489e83099782d51d7b55",
+            "202cb4369e4845a6a60408400f88b0ed",
+            "92c719b392564d339ff73ccc83c966d0",
+            "938da511fca04f77af54fe3b34287e6c",
+            "3f2d02e521e848398853c526866d3585",
+            "ce963a069b50408abc6cf6073857c5ee",
+            "21d179e89c8d47768585c9d9d3bd6e20",
+            "f88cf9ec7d8b4faa80017e24f99d5dc8",
+            "7a20309eef57435f9f35082d5285f444",
+            "6d669ab16e374f0faa089a183bd52532",
+            "7d207f93b4a24696abf379bcc01723dc",
+            "b0ab92d005974b959f7cb0f2cb9b11d6",
+            "7b93f73af3274920ab2b51418e95cff6",
+            "e4dd0f4da33c453e886144de5c93aeb3",
+            "6d34020216d74b588708e9c9f33f800b",
+            "b0ee851984d9431597446f79d656d64a",
+            "c75e6f8363fc4bd1ab7d1c6513f60dd5",
+            "56c8c883282e4f74ae1c353455136380",
+            "e13b3d868fe3450cac508a8799743696",
+            "3a1168d83bbd44c887b93d20f8eb59a6",
+            "64f05915a7b040f9a73dfba9e02d249d",
+            "5ec271f8377a43878a090aaecdde01e6",
+            "8473ba1cc0d44bba85462cdbf12e9514",
+            "2a058b66d21642f3ab38b917a57ead4c",
+            "0eccda6238eb4756863a6efeeadc9efb",
+            "4db3cc54264240ccac6402b67dfa1049",
+            "ec11d0d99c684e2c87c1bf1c05220a95",
+            "84a6704158ab4806a23226678b1be9a8",
+            "7b6f963d98df4d36b01e21a89fafd957",
+            "19026bb7f79446bc970e1210cccf206f",
+            "e45b9b8af30042d0a0f91ef4ec1aad76",
+            "3735eff345c9459a986b52ac7c469a33",
+            "7d99b26699f0438ea804db1871d2a172",
+            "791025ac27604718a24542401ab225e2",
+            "230aa7332e4e4114a923b317b4e71991",
+            "45b9943cd00546afad178c901cd94ade",
+            "11e6194ce58c4c05a4cf3c9c55b4acc4",
+            "5f177c38708d4492909da4b8ae0a4120",
+            "b9b02352a20e45ac8128f58b9387435d",
+            "07054014fd004b44993a392856f25f58",
+            "b4afe9af86d1487cbe0cb9f4956db2e2",
+            "abd398c4b93343a49f7882d3b141ccf4",
+            "3fda98dab7574ba489090143ce8a0e82",
+            "8b00742b502d493094ad605fc90b5b09",
+            "e05ca35fa13a42e0bfb8daef4706d291",
+            "a27fc920f8c94953a0c3e9b2120f1b86",
+            "722dd7a1bb984a22ad1b4da14741d7fd",
+            "7c8f64cb9eda44eca40a6ef5a203afc0",
+            "10aad821076a43b88b833f52d41df0ef"
+          ]
+        },
+        "id": "HRyAujuuw0IG",
+        "outputId": "d806f452-f0c0-4571-ed6d-a568be3106fb"
+      },
+      "outputs": [],
+      "source": [
+        "from transformers import DonutProcessor, VisionEncoderDecoderModel\n",
+        "\n",
+        "processor = DonutProcessor.from_pretrained(\"nielsr/donut-demo\")\n",
+        "model = VisionEncoderDecoderModel.from_pretrained(\"nielsr/donut-demo\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "r5uhIMxCw-ZI"
+      },
+      "source": [
+        "As we don't have a test split here, let's evaluate on the validation split.\n",
+        "\n",
+        "We'll use the `token2json` method of the processor to turn the generated sequences into JSON, and the `JSONParseEvaluator` object available in the Donut package."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "EDdzbjIOuCfI",
+        "outputId": "702b39c7-5e75-4072-fb6e-965b899314b9"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install -q donut-python"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 123,
+          "referenced_widgets": [
+            "674feecda5844fc8b669e8153a982b3f",
+            "9ed0a46f8705464f81f2c8e1a4b8cc89",
+            "0f6e284513e94a3f8681d4b4e39fcb54",
+            "7208cb24790c447aae18746d11b7cc7e",
+            "c1fe650a41b14253b0c398f09293310c",
+            "a105133b82344a97b79250d8cde50f74",
+            "c474aabdf84b459aae6c9c0de4526b47",
+            "75a3f953de714650a03ad3b2319f8a82",
+            "b49ab085f6e04c7398e90e09eda48c5a",
+            "0755ff4ddf1c453f8f6ca501001fc486",
+            "43d49626f9284b23b3bca84aaf9f4616"
+          ]
+        },
+        "id": "PZSG38-10YVL",
+        "outputId": "ca551149-e451-4233-ab31-5d9d7bcc818f"
+      },
+      "outputs": [],
+      "source": [
+        "import re\n",
+        "import json\n",
+        "import torch\n",
+        "from tqdm.auto import tqdm\n",
+        "import numpy as np\n",
+        "\n",
+        "from donut import JSONParseEvaluator\n",
+        "\n",
+        "from datasets import load_dataset\n",
+        "\n",
+        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
+        "\n",
+        "model.eval()\n",
+        "model.to(device)\n",
+        "\n",
+        "output_list = []\n",
+        "accs = []\n",
+        "\n",
+        "dataset = load_dataset(\"naver-clova-ix/cord-v2\", split=\"validation\")\n",
+        "\n",
+        "for idx, sample in tqdm(enumerate(dataset), total=len(dataset)):\n",
+        "    # prepare encoder inputs\n",
+        "    pixel_values = processor(sample[\"image\"].convert(\"RGB\"), return_tensors=\"pt\").pixel_values\n",
+        "    pixel_values = pixel_values.to(device)\n",
+        "    # prepare decoder inputs\n",
+        "    task_prompt = \"<s_cord-v2>\"\n",
+        "    decoder_input_ids = processor.tokenizer(task_prompt, add_special_tokens=False, return_tensors=\"pt\").input_ids\n",
+        "    decoder_input_ids = decoder_input_ids.to(device)\n",
+        "    \n",
+        "    # autoregressively generate sequence\n",
+        "    outputs = model.generate(\n",
+        "            pixel_values,\n",
+        "            decoder_input_ids=decoder_input_ids,\n",
+        "            max_length=model.decoder.config.max_position_embeddings,\n",
+        "            early_stopping=True,\n",
+        "            pad_token_id=processor.tokenizer.pad_token_id,\n",
+        "            eos_token_id=processor.tokenizer.eos_token_id,\n",
+        "            use_cache=True,\n",
+        "            num_beams=1,\n",
+        "            bad_words_ids=[[processor.tokenizer.unk_token_id]],\n",
+        "            return_dict_in_generate=True,\n",
+        "        )\n",
+        "\n",
+        "    # turn into JSON\n",
+        "    seq = processor.batch_decode(outputs.sequences)[0]\n",
+        "    seq = seq.replace(processor.tokenizer.eos_token, \"\").replace(processor.tokenizer.pad_token, \"\")\n",
+        "    seq = re.sub(r\"<.*?>\", \"\", seq, count=1).strip()  # remove first task start token\n",
+        "    seq = processor.token2json(seq)\n",
+        "\n",
+        "    ground_truth = json.loads(sample[\"ground_truth\"])\n",
+        "    ground_truth = ground_truth[\"gt_parse\"]\n",
+        "    evaluator = JSONParseEvaluator()\n",
+        "    score = evaluator.cal_acc(seq, ground_truth)\n",
+        "\n",
+        "    accs.append(score)\n",
+        "    output_list.append(seq)\n",
+        "\n",
+        "scores = {\"accuracies\": accs, \"mean_accuracy\": np.mean(accs)}\n",
+        "print(scores, f\"length : {len(accs)}\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "hN-FiUAJy1YX",
+        "outputId": "e8943e8f-a936-4c00-8f96-a055924ec8ad"
+      },
+      "outputs": [
+        {
+          "ename": "NameError",
+          "evalue": "name 'np' is not defined",
+          "output_type": "error",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+            "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMean accuracy:\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[43mnp\u001b[49m\u001b[38;5;241m.\u001b[39mmean(accs))\n",
+            "\u001b[0;31mNameError\u001b[0m: name 'np' is not defined"
+          ]
+        }
+      ],
+      "source": [
+        "print(\"Mean accuracy:\", np.mean(accs))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "3R6rov0i0bkN"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "accelerator": "GPU",
+    "colab": {
+      "authorship_tag": "ABX9TyMs0jX0vkostGjO0/wWd8Do",
+      "include_colab_link": true,
+      "machine_shape": "hm",
+      "provenance": []
+    },
+    "gpuClass": "standard",
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.8.10"
+    },
+    "widgets": {
+      "application/vnd.jupyter.widget-state+json": {
+        "008e77e9b3cb4cc4b37e875cab3f3d6c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7d77a9f92e984ac7b9350addc57cb577",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2d476a17141343508bcac54393555e9b",
+            "value": " 100/100 [00:01&lt;00:00, 93.70 examples/s]"
+          }
+        },
+        "0098775e311344f681335445edadd72f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "009ae1d114cb48d0990e934e19ee961f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "00d41781e51e4adb823c44a68727693a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "012b26d0aed048628e59dbb0c02f76e0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b132e3a6f07e452382eadbedff054b94",
+              "IPY_MODEL_3920ef1a0817495696b874cc61516d7b",
+              "IPY_MODEL_24d17f7c48fb4d41b02ec4731d629758"
+            ],
+            "layout": "IPY_MODEL_d91e67e21bfa49888bf6316c154bcf77"
+          }
+        },
+        "01b01e7329334686ba39c11ec18e9df5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "02700c32e4d64a66818ac92209384b14": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2d4f64a23cc846a48f0906c74d1502b9",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c6e2d6abd785494ca143b5978811c326",
+            "value": 100
+          }
+        },
+        "03a5186fafe7424c896a5c8f4b356098": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f1a2bee7a7dc408087833912c951119d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8eef683c23a14e9ca9cc8e260a8d25aa",
+            "value": " 489/489 [00:00&lt;00:00, 8.52kB/s]"
+          }
+        },
+        "0459618abd954a9a95c3eb137954523c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_5947ad0e06a54e38b8d09d160bffb0d2",
+              "IPY_MODEL_5cc9c7f2db1846b6905452d7a9568919",
+              "IPY_MODEL_dd0b6870c8b6435691009ca66fa71b09"
+            ],
+            "layout": "IPY_MODEL_c663b10ffce1432c89a3948e324571b0"
+          }
+        },
+        "047bdaa0ff9d4a4f8d6f46fca23bd0d2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "049b89f7db7b4b278b2b266771a22ef1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "04b01b03fcc143fa8633b52ec231f026": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "04fa08f418e74bfe8d274620cd07e448": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d1837ece0226413489f3df0dfd7f3279",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b0095f1cb2364fc991f05f312656947f",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "053e5fb5ff954b1bb8099c07ad77c35d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "05c1c99b4aff486a9c5eeadf9bd8230a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_72254d54d49a4054b49882200eecc49b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_cfa9b34f74b541fc9c54b905cffa05ad",
+            "value": " 1/1 [01:03&lt;00:00, 63.26s/it]"
+          }
+        },
+        "07054014fd004b44993a392856f25f58": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8b00742b502d493094ad605fc90b5b09",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e05ca35fa13a42e0bfb8daef4706d291",
+            "value": "Downloading: 100%"
+          }
+        },
+        "0755ff4ddf1c453f8f6ca501001fc486": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0759cda7bd084b02921689bc5e319ba5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_31081f8d85954a33bcc789b1f5f93c56",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ec2fc9e744d9460f9063f9c0aac4c3d5",
+            "value": " 1/1 [01:03&lt;00:00, 63.02s/it]"
+          }
+        },
+        "07a8d73caf1741d78f637c5093884834": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_938da511fca04f77af54fe3b34287e6c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3f2d02e521e848398853c526866d3585",
+            "value": " 4.02M/4.02M [00:00&lt;00:00, 14.3MB/s]"
+          }
+        },
+        "07acf858ebad4351bfd3cfdb339dddcb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "07b75ae72a6a4d16a3ff73a1debe2ee5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1cda98448c074471ae879ab9410e49d5",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_9a7cb4d7e9514575a93e2f86fc32fb4b",
+            "value": 100
+          }
+        },
+        "082d0b472b90409f8ab9b02391df63a4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1c7a17fb7dd041c2949e5df85ee78570",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c6e7bfb4e3144b16bcfd3fd12673d853",
+            "value": " 100/100 [01:21&lt;00:00,  1.22it/s]"
+          }
+        },
+        "083ca4f1dea5421bb07bf9cfc802871d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b71da8215fd74394aeef7b2835ebdce2",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_aad2e43eeafa4cccb5e476d3fce4dacb",
+            "value": 100
+          }
+        },
+        "08c07275cbbe4fd0822c354d99c303ea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "098aae301ab04e688652dd0c05f8de1c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_10d449f46d9c4502baaad1606f873c09",
+            "placeholder": "​",
+            "style": "IPY_MODEL_44b4f06f3c0841d2ac960337d18de7a3",
+            "value": " 100/100 [01:25&lt;00:00,  1.17it/s]"
+          }
+        },
+        "09c44c23e97c4293bc1d30f234634c42": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_00d41781e51e4adb823c44a68727693a",
+            "max": 441418432,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_d56998a0695e434bb7fe3857f5075083",
+            "value": 441418432
+          }
+        },
+        "09e57cfef8d04198b07337e6adfd3cfd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3b5d54289850421e821f88fc5f0c0421",
+            "max": 362,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_bcaced45f306473887ab7c07df871481",
+            "value": 362
+          }
+        },
+        "0bb2e5d6e3544a44940c79b7a5543407": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8eda879a6d224fb091f538c2806d7890",
+            "max": 3,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c34474a8f453410f8f3dc39c835e3a2d",
+            "value": 3
+          }
+        },
+        "0c44b50f550a42d5a89d35c0233fa0bb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0c565bd0bd89433286f309c0a728e020": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_9ab3a07b87854294b687ab1bd1ce2fe1",
+              "IPY_MODEL_61c95b7243604620a9151ce8b6fcc910",
+              "IPY_MODEL_f21af123c24f43498942dd4f3e91c54f"
+            ],
+            "layout": "IPY_MODEL_f6c554c9119f4152bd747905b3b2ade3"
+          }
+        },
+        "0c9bb2443ecf460a876558b547c3b97f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0ce302531a69423aa36a39e0502f7970": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0d29cb058287441397849858958eecc5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5cf9cf4d06af477aaadf2c2eafb21a0f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_acb18d163a98436abc6a34c80d0b9875",
+            "value": ""
+          }
+        },
+        "0d2f68be02e7495fab83926f99b93586": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bfc5138baadf4385a0ed6b87107fabec",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b760aaf9ca3047378404f446549355ef",
+            "value": " 477/1300 [05:37&lt;09:42,  1.41it/s, loss=0.301, v_num=n3o8]"
+          }
+        },
+        "0d5904889d6246e4b0bd8223d9ce79ab": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8b4f59bf71c64c2293a9e089b963b914",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7372f1fa693345ad8f26f0148b2f527b",
+            "value": "Downloading: 100%"
+          }
+        },
+        "0dfe3ae073634ba8a1747bc96b30e2bd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0e2de7dbc3f3450bb17060ce2687c3ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_44a17877ab654e0481b0fe827a991e5a",
+              "IPY_MODEL_083ca4f1dea5421bb07bf9cfc802871d",
+              "IPY_MODEL_8249f31d416e4ed388233cd633c212a7"
+            ],
+            "layout": "IPY_MODEL_de3f7930ae454905be655bf33f045280"
+          }
+        },
+        "0e590d1bb05d4bfaa6c0c41cb41e4794": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "0eccda6238eb4756863a6efeeadc9efb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "0f2dc68b57614e79b95ddeb715f124af": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "0f6e284513e94a3f8681d4b4e39fcb54": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_75a3f953de714650a03ad3b2319f8a82",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_b49ab085f6e04c7398e90e09eda48c5a",
+            "value": 100
+          }
+        },
+        "0fb032afb0904c358aaa984c8556d0c8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "0fe66bd8c6314fdb86ea236d9638f538": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "0fedf481a76a4d319ddc6afe51345a36": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "10153cc99ab24f089bc2c964eb5f4806": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "107117ee9e3947058cf7586eba69cf6e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "10aad821076a43b88b833f52d41df0ef": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "10d449f46d9c4502baaad1606f873c09": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "10e6ba61808f471d82b431c607b65d99": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1105d8a1da0146e0963254b901f6fd80": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_439674cf49124161b3783a681b407ed2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_10153cc99ab24f089bc2c964eb5f4806",
+            "value": "100%"
+          }
+        },
+        "11e6194ce58c4c05a4cf3c9c55b4acc4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "12636a29bb09482693911ac3c6ab429a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1355cef1e865410182443c3b8ba73fd2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1384b04401ee4d5e9a7ab9574e660ee6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9db7c2d529ea46d48e22271d8432f137",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6d6241a0e8544b03bd406739bd2e3914",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "140f7d5cb0fb4b4b8598d1552a429052": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a4eacb994f2147d29d2d68e9b3c456aa",
+            "placeholder": "​",
+            "style": "IPY_MODEL_205926dbd19445c08bd1b8a02e33634f",
+            "value": "Downloading (…)ncepiece.bpe.model&quot;;: 100%"
+          }
+        },
+        "144c2d74865e41c19a4a6efb4b120ca9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "144e18e547844b1789fa6759bad4b1a2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6fcd1c300caa489dadeaa50c6c814a14",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_f60b9e69e69e40189644c2cde41fae18",
+            "value": 100
+          }
+        },
+        "148b60b8a9a44244874d2db13de48a00": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "1510960e07b742c4b1d838b2d533439b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "15799ffca3624428926e2ddb16728b68": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "15f7ce33a6304293939d23084881a33e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_414f4fac280c49db98080b31e3facc69",
+              "IPY_MODEL_3752aef8ee5147e2b603a691f233cc24",
+              "IPY_MODEL_45ce4745da5840a090620d59ce4eb1e5"
+            ],
+            "layout": "IPY_MODEL_c3f54d242da14b689f6e213867b81cec"
+          }
+        },
+        "1646a7c133a94af7bcfda5fb6ca800bc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_80cc4498465e4fecba040320c9bf1af6",
+              "IPY_MODEL_55e69f30eb7f44dfb9fa64f938cd41dd",
+              "IPY_MODEL_ea7c0bd905074e5d8105bb82036bea1c"
+            ],
+            "layout": "IPY_MODEL_e529a78e1aba43d980b2953aef3cdfba"
+          }
+        },
+        "165a9c0135cb45869feb49beacb8101a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1674e26429bc4c80991bb8942b56a7d7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c97025e7d015445fafa406c4c1a89af7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_1dc7760bdd2944ad9c4991c82dc86e25",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "167cf75950f6434293f6809a84f998f3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "16ea181fc8694d29b499b46678fbdaf3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "183c1ce81c8544719ce85a79cf44f9e9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_538e66a6277b478db47627b3f38b7da0",
+              "IPY_MODEL_7de626274586484c966e3fcd322559af",
+              "IPY_MODEL_07a8d73caf1741d78f637c5093884834"
+            ],
+            "layout": "IPY_MODEL_049b89f7db7b4b278b2b266771a22ef1"
+          }
+        },
+        "18db9e56c0354600851d762c8de0f774": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "18e8af9f9ff247c88797e03d48b675f9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "18f20450f84d48d7839bb3c676cb53d4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_75469c205b314779aef9d1e7ff2fd612",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2dd3e0f914f6471587bbe40beeacd7f3",
+            "value": " 100/100 [01:23&lt;00:00,  1.20it/s]"
+          }
+        },
+        "19026bb7f79446bc970e1210cccf206f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_230aa7332e4e4114a923b317b4e71991",
+            "max": 4900,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_45b9943cd00546afad178c901cd94ade",
+            "value": 4900
+          }
+        },
+        "1a457a54c55f4aab95a9c3cfaa2a23b5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1b07db1c1be94ffe98ca2e23ca97e187": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ed76219299d54f908eff9c9678e1e00f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_76839f93896d43dabcb10f14b031c037",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "1c1855ade6204625bfaab54ca2159af5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1c2bd9e72e334917b3ce39810bf5ea0b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "1c7a17fb7dd041c2949e5df85ee78570": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1cda98448c074471ae879ab9410e49d5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1d3f96ad71b74c31b18b50d0dafefb6e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fe170e9c276f49b6927ffcbf3809de3e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_07acf858ebad4351bfd3cfdb339dddcb",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "1dc7760bdd2944ad9c4991c82dc86e25": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1df30bb3175541a7b7a6541b38d51b89": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "1e25f97059cf482587bc1dcb055d4f7c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "1e6e26bf5f3e4322b0f9ff4352976adb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5c6c3811d9e04247abd52e0f835b6a5e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fdf8fb828c1d4ad6b864b9197a0aa486",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "1eecabada33e46da975375f9fce5517e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_1674e26429bc4c80991bb8942b56a7d7",
+              "IPY_MODEL_72e608fe672b40c99de89ad5ce1e33c0",
+              "IPY_MODEL_a35f8906c1ae46828120319694065815"
+            ],
+            "layout": "IPY_MODEL_6340e0aa27c04db0b48448513e9875c4"
+          }
+        },
+        "202cb4369e4845a6a60408400f88b0ed": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2040593b2df341c68670f38512b423d0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "205926dbd19445c08bd1b8a02e33634f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "20e0bf2b09d841d6bc9e1f36ec4079bc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "20eb3303eb2b429891247566f52218c0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "210766df14774c1e89d0df73f294daa6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "212fc0393d3a4ea9a76571c9b636ae20": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "21d179e89c8d47768585c9d9d3bd6e20": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7d207f93b4a24696abf379bcc01723dc",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b0ab92d005974b959f7cb0f2cb9b11d6",
+            "value": "Downloading: 100%"
+          }
+        },
+        "230aa7332e4e4114a923b317b4e71991": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "23e4cf09102a4753844ceed08a211d53": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2472d601c42041e6acb51d19de547a0a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "24b5e61aecd84402a6261b4b06146559": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bf9d9715e7684c4e8ac29cbcabf1c600",
+            "max": 809404185,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e71b1fe193ba49afb42fe50f96663070",
+            "value": 809404185
+          }
+        },
+        "24c7acb091ab4037a6b4a2eb8a1085e3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "24d17f7c48fb4d41b02ec4731d629758": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3335761da6f84b2bb970a32f27f5abc4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_69f55ea05abe4ca9b21135169edc7a71",
+            "value": " 800/800 [00:08&lt;00:00, 90.56 examples/s]"
+          }
+        },
+        "24d1c38ed9e241c2b13abd30ead9a8de": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_eb5f6ef011b44f7d8a62a35ee66899db",
+              "IPY_MODEL_0bb2e5d6e3544a44940c79b7a5543407",
+              "IPY_MODEL_5517cbf80d8b448d9a511070dfb4dc1d"
+            ],
+            "layout": "IPY_MODEL_107117ee9e3947058cf7586eba69cf6e"
+          }
+        },
+        "24e315cb82a747d6b9566b461db6aee9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f98e3325c6b64df7b028a71eb6c1aa5e",
+            "max": 1300,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c5f481bd341a48668518912efbd6a35a",
+            "value": 477
+          }
+        },
+        "25296141a79c4477aac6635dd30a80e5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "25721e39542d43029d26ac34b4af6d89": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "257fa5076dd74486b7751bffa39c2ef8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b3a98298b4ea434da0d8815ba0f2c4a4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e6523a394c4442bd949cae3f7666b6d4",
+            "value": " 4.01M/4.01M [00:01&lt;00:00, 2.27MB/s]"
+          }
+        },
+        "259d3cba0a5b4943b4b025f921edf06b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "259d56ea4f394fe591b26941164dcae9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "262f11dfba44467c882893cec6523189": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "26bb592b09c94ba081cd1f913c318f73": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2781fb98daf147638db891d565d2f194": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "279ce49322904b87b2ec18b4f497465c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "293e17ab3b4a462ba7d4adc2de35aa05": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "297ba8af5a704c5ca34d0f406de3e918": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "299e59499eda4a1db01880e4fb1d5cd2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2a058b66d21642f3ab38b917a57ead4c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2a459b1c958240d89f753fe695b457e0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2aa84a0d65254ef49ee100f66e393ae9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2b1ecdea6e49453588fdca19fc19eaaf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2b8a201c62c241a89625630f550f6c02": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2ca98f8a45fb4335ac197e9b7c019e41": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_6d146fd4003e47978a253192463dd514",
+              "IPY_MODEL_33596291f0c344ad9219c9a7eb6c5c90",
+              "IPY_MODEL_30374f50d4af4b9598cb13823ad7780c"
+            ],
+            "layout": "IPY_MODEL_6c9cca8ae41441b29f2dd7ac81cd35d4"
+          }
+        },
+        "2d476a17141343508bcac54393555e9b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2d4f64a23cc846a48f0906c74d1502b9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2dd3e0f914f6471587bbe40beeacd7f3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2e682e41d92343b792991eaa2b72d7de": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "2e6a63d04fd747a280f813b1335a52b1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "2e8a6bd2ef104b32868443ac711c88b6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "2ee2d4a8635f45dba573b749244f9e2a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "30374f50d4af4b9598cb13823ad7780c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6a3d2f0a94ea4f72bc81400880f8c430",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c3735a62d26743cc88f0bb71712edaa2",
+            "value": " 809M/809M [00:06&lt;00:00, 137MB/s]"
+          }
+        },
+        "30f78b0e910549a6a5e79e8a49c4c67d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b12a725c43db4fa4ad13d82c75738994",
+              "IPY_MODEL_144e18e547844b1789fa6759bad4b1a2",
+              "IPY_MODEL_cdf0d854eba142779798e0ac495c02af"
+            ],
+            "layout": "IPY_MODEL_bfc6976f3a4b4de3bd42aa1dc9ab73e5"
+          }
+        },
+        "31081f8d85954a33bcc789b1f5f93c56": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "311acaa0e5844400b54281fe18b50b34": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "314069aa673f41f9abd2c6d2b634a64c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_7df7c889e4794145ba5b20177df36189",
+              "IPY_MODEL_f16c7f25616a478ab6ba69ce88a69724",
+              "IPY_MODEL_e9b2a001c8dc4591b00a21893c56dceb"
+            ],
+            "layout": "IPY_MODEL_96b45a24defe461998123ec31aba1d97"
+          }
+        },
+        "31d2bbdfa41b451eb71eba642b3db4e4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "31d5cb042096428fa4e8a0cd682ddc09": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "324b10e8d5ea4f1598111ce9321f5809": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_311acaa0e5844400b54281fe18b50b34",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6016947c02af4021851e950c72479029",
+            "value": " 100/100 [01:22&lt;00:00,  1.21it/s]"
+          }
+        },
+        "32cb9bbc1e4547cfbe4df1e4ca70e254": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "330b85404fe84761a72a8cbfb696eae1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "33170adc2cbe4b3daa9073cee501d854": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_583a3d03b1f344d6b7424589c4db1634",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_56628597cea5425684265b293010eefe",
+            "value": 100
+          }
+        },
+        "3335761da6f84b2bb970a32f27f5abc4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3350308cf34f4c02bd89f6e2a345ed12": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "33596291f0c344ad9219c9a7eb6c5c90": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fe5fe724aaa14f2bb80e84fc589103fc",
+            "max": 809168699,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c65a6cc99b06467cbc7f4efe8d80aae0",
+            "value": 809168699
+          }
+        },
+        "337672b1b8894951810dc1c645f66dbd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "33a65dc99580418cb494e29ae5a0fb9a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3427bc46e6f84ac5a403b42afcde9b08": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "LabelModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "LabelModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "LabelView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4a86c267cbe34ba3bbe0ec2e0035bbbb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3bcce8d28d894837824f52bae420976a",
+            "value": "Waiting for wandb.init()...\r"
+          }
+        },
+        "3475f0d8415b4f3ba6b5ad701c365e61": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3528f8245a2044c4b2037481bdaf39a7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "35560ff2bef140aea29689440aa8f741": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f794d85eed554a6ea4dabf8420da0160",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f6679d2887ae4c759e6fe58b01a9d546",
+            "value": " 6/6 [00:06&lt;00:00,  1.04s/it]"
+          }
+        },
+        "3563de5d5e394c578b7667bdae8644e6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3612afa317c5414bbffdbc1f241eb133": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "36777dc617bf4589a8ab9802f363ecf4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8cef8071dc984acc8a003134e8d64a11",
+            "placeholder": "​",
+            "style": "IPY_MODEL_cd80b89157374e759c3a24091fced46b",
+            "value": "pytorch_model.bin: 100%"
+          }
+        },
+        "36c149d0545d43d7ac1cb34f4e3c33bd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "36c215478b2f415e904a24de4b91d9d7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3735eff345c9459a986b52ac7c469a33": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3752aef8ee5147e2b603a691f233cc24": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_618716c2a7dc4557873d08a9ea2b0b22",
+            "max": 234202795,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_663d883b5cbf4a6998db3319c55ee3d8",
+            "value": 234202795
+          }
+        },
+        "37c969be0a7946c6a7d45940fcde5cf9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3880476d3f0e4962be29180763486deb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f24b9f61a1fe4c3f86e5086676a5e5d5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8299c1ef69414603a1604699c777e1f4",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "38fff333701c4678b5c69863aa8992ac": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3920ef1a0817495696b874cc61516d7b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_be37899db94d4c15b8e194c03b057a45",
+            "max": 800,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_4ec3f7acd47c476fbf7e030426c51a7a",
+            "value": 800
+          }
+        },
+        "394b5ca6361e4d38ba6cca638de5cdcb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3a1168d83bbd44c887b93d20f8eb59a6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4db3cc54264240ccac6402b67dfa1049",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ec11d0d99c684e2c87c1bf1c05220a95",
+            "value": " 355/355 [00:00&lt;00:00, 5.12kB/s]"
+          }
+        },
+        "3a6dce72d0ed40c48bbd91b3f07aa67a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_36777dc617bf4589a8ab9802f363ecf4",
+              "IPY_MODEL_f2e58d8539584eebae048ed68d50a641",
+              "IPY_MODEL_9dde5575c8e7438fa2d86e4b9a4fb33f"
+            ],
+            "layout": "IPY_MODEL_18e8af9f9ff247c88797e03d48b675f9"
+          }
+        },
+        "3a78f6a7e4814c23b19458c6f2857754": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3b5d54289850421e821f88fc5f0c0421": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3bcce8d28d894837824f52bae420976a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3c7e904af22f42dca56b6421d35412ff": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3ca24d66c54b42868c814abb11d4214e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3ce6f898ce604f258efab30dd9f65b79": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ac08a565f2d5447a95d2e6af307f3f09",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4ed83abdd375497f9edb35c828d70be7",
+            "value": " 4.74k/4.74k [00:00&lt;00:00, 212kB/s]"
+          }
+        },
+        "3da1fd9a348f4c7bb07889c017cc0c2a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0dfe3ae073634ba8a1747bc96b30e2bd",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_9dcbe88c6ba446ea9584331776d2748a",
+            "value": 100
+          }
+        },
+        "3db9e9823c2d4f418cd6707058ff07ba": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3e528e7f8cbf4ca597c63d1789a556a5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_4184d862482d4589806f8d09b5b85737",
+              "IPY_MODEL_c99fc92b5c87414faa6bafd1d91ce9c4",
+              "IPY_MODEL_098aae301ab04e688652dd0c05f8de1c"
+            ],
+            "layout": "IPY_MODEL_aff4e5ac7e384d408fc23ca0a8d3658f"
+          }
+        },
+        "3e8e09b6655a4c8fb3995915a69c795f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3e9927167bb84cac9cf56f350bee5aae": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "3f10740717d4479ba2acf18f7957fc44": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "3f2d02e521e848398853c526866d3585": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "3f76ca5381b64731af382a63b890292b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d3995239fdf54fabb7fb42417dd2d1e2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_32cb9bbc1e4547cfbe4df1e4ca70e254",
+            "value": "Upload 1 LFS files: 100%"
+          }
+        },
+        "3fda98dab7574ba489090143ce8a0e82": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "404fed29990348b7ac2fba4a5b61aa89": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4058a3b2505f441f84f78fe4f7188aa8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_10e6ba61808f471d82b431c607b65d99",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5c9eb0211674488bbe8ec74c68a6e9a3",
+            "value": " 100/100 [01:21&lt;00:00,  1.23it/s]"
+          }
+        },
+        "414f4fac280c49db98080b31e3facc69": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ba402e291fd94f8ab8f1a74c5c1ac551",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fe92ba127a624524bfe051a6040b4c45",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "4184d862482d4589806f8d09b5b85737": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c0cf700f7872458385250ba075a8edb1",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2e6a63d04fd747a280f813b1335a52b1",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "422523d56ec74035b0a55b9c97d1ed19": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "439674cf49124161b3783a681b407ed2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "43d49626f9284b23b3bca84aaf9f4616": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "44a17877ab654e0481b0fe827a991e5a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5628c489cf31430c8b7efe8118c64815",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b04b0c322c624afa8bb5a128b2af08b6",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "44b4f06f3c0841d2ac960337d18de7a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "45684f2d86954453b3f7059f847028c4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cc2651a0102d49c7b6a9ac6e82db8c9a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3a78f6a7e4814c23b19458c6f2857754",
+            "value": " 3/3 [00:00&lt;00:00, 76.29it/s]"
+          }
+        },
+        "45b9943cd00546afad178c901cd94ade": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "45c29055f8a74361b562fb2baaa3b71f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "45ce4745da5840a090620d59ce4eb1e5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_337672b1b8894951810dc1c645f66dbd",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2b1ecdea6e49453588fdca19fc19eaaf",
+            "value": " 234M/234M [00:03&lt;00:00, 72.9MB/s]"
+          }
+        },
+        "45df3e9080c7437680d57cb5936dc1de": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4619abf6125240f7862c7583a6f68af1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "4664a4a1ab034098a12b6ad238c0391b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f8c2d38923c948cf8f2cf8c49ffb2c8d",
+            "max": 4011031,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_37c969be0a7946c6a7d45940fcde5cf9",
+            "value": 4011031
+          }
+        },
+        "484fac29339449d58309c92dbbbd2af2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "487685e439f647efbc2350f87ae5d275": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "488139fa453f40e6895a0bac7d5cf840": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4a2f2fa2885347aebb436467a49b8857": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4a86c267cbe34ba3bbe0ec2e0035bbbb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4a987dc4a0e54e5da442be8d6a1c7f09": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_279ce49322904b87b2ec18b4f497465c",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_15799ffca3624428926e2ddb16728b68",
+            "value": 100
+          }
+        },
+        "4c06e9c680b6471c8305042a7e3757e3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4cacd92cb1f04dcea344f93e816d6244": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4d6704d874404c9996e32b16b7773169": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4db3cc54264240ccac6402b67dfa1049": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4ebee50caff240aea9377fa4a2d0d7cf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4ec3f7acd47c476fbf7e030426c51a7a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "4ed83abdd375497f9edb35c828d70be7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "4f2be832c1f04902af8bfc4f5d971057": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "4fefc71218894bd4a6b2e95ff3a882e5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5053663ab6874c378d764dc8584b6aca": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_932854c5974142b3b906ac1db17725fc",
+            "placeholder": "​",
+            "style": "IPY_MODEL_baad5e47bfc940229c7c19cb8372b59c",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "507d4fec2b8847d79a884853b4d81dad": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "50ce7fc092624343a610286377ecd39a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_840a81ea307a4633bfd9846f89121257",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7a2a38deff05410b92c7f0aca5e2f906",
+            "value": "Downloading (…)cial_tokens_map.json: 100%"
+          }
+        },
+        "5253bf28cfe948fd8520b5aefd5cdeff": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "52cbbbf6bc6643e9b43d844586ab453e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "538e66a6277b478db47627b3f38b7da0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_53f439b9ac714080972b77d4ce2e15ed",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8d98ed226dd1489e83099782d51d7b55",
+            "value": "Downloading: 100%"
+          }
+        },
+        "53f439b9ac714080972b77d4ce2e15ed": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "542c34c7d55c400a8f623232403fe250": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_56959726851f49a9b05b1b92cfdd6e74",
+            "max": 1,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3f10740717d4479ba2acf18f7957fc44",
+            "value": 1
+          }
+        },
+        "543c3f05eb0547298950b7e7d8c64467": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "548572561a0045b485ef9dde63326446": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e30df53a96fc474da072e8692a0d1d58",
+            "max": 27,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_8c3fc7e7b9354d0fb59602100bc5ab1f",
+            "value": 27
+          }
+        },
+        "54e45826ac5f44d3b315e59391fbc347": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5517cbf80d8b448d9a511070dfb4dc1d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1a457a54c55f4aab95a9c3cfaa2a23b5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fe52a9c056f843068d5588e488f490db",
+            "value": " 3/3 [00:00&lt;00:00, 147.78it/s]"
+          }
+        },
+        "5536aeeebaad4d158a11a706940a0220": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "VBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "VBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "VBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_3427bc46e6f84ac5a403b42afcde9b08",
+              "IPY_MODEL_b294221a318349228f631ca89407740b"
+            ],
+            "layout": "IPY_MODEL_45df3e9080c7437680d57cb5936dc1de"
+          }
+        },
+        "554913277fc34084990cd041ca766701": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "55e69f30eb7f44dfb9fa64f938cd41dd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_404fed29990348b7ac2fba4a5b61aa89",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_9b045fecb5c24541b6611ba71237f6f7",
+            "value": 100
+          }
+        },
+        "561abfbe2ed9405d8bc9c67f3a4c4c8a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_259d56ea4f394fe591b26941164dcae9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_31d2bbdfa41b451eb71eba642b3db4e4",
+            "value": " 441M/441M [00:06&lt;00:00, 49.4MB/s]"
+          }
+        },
+        "5628c489cf31430c8b7efe8118c64815": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "565a3479b2f140c4bdba43ba99d71c2c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_fa5080966e724cf2901654c57dbe8abd",
+              "IPY_MODEL_6394dfa7856b4bf49a9325f22dfe1cc1",
+              "IPY_MODEL_baa432ed76ae437e8946ebe41301453c"
+            ],
+            "layout": "IPY_MODEL_6ce260c95cfa4736a22d77f5faba3888"
+          }
+        },
+        "56628597cea5425684265b293010eefe": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "56959726851f49a9b05b1b92cfdd6e74": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "56c8c883282e4f74ae1c353455136380": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5ec271f8377a43878a090aaecdde01e6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_8473ba1cc0d44bba85462cdbf12e9514",
+            "value": "Downloading: 100%"
+          }
+        },
+        "56fea1b142db47fbab0b118185587e76": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "582d8cd7787443f59398e2f79c328b51": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_554913277fc34084990cd041ca766701",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e8f2e16d8a9f4091a2d6438892c731b4",
+            "value": 57
+          }
+        },
+        "583a3d03b1f344d6b7424589c4db1634": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "58a4b18d859e4c47bc97f2e6ce8c6c73": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a7fb70b9171c4958bc5f5c37e51f8cd6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_31d5cb042096428fa4e8a0cd682ddc09",
+            "value": "pytorch_model.bin: 100%"
+          }
+        },
+        "5915cae6f7ba4d5caa52ff5c8f854b38": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_487685e439f647efbc2350f87ae5d275",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ca6fcf9c01fe4f2db382b6b0f8cb169d",
+            "value": " 456M/456M [00:27&lt;00:00, 17.4MB/s]"
+          }
+        },
+        "5947ad0e06a54e38b8d09d160bffb0d2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ebeb73a097574a8597d3592329674e44",
+            "placeholder": "​",
+            "style": "IPY_MODEL_81255865450c47ea8a9de6b7996514a3",
+            "value": "Downloading data files: 100%"
+          }
+        },
+        "59585c4440a64e1fb76601df8aee255d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5af452039cad49ee92c938aaffa25765": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3e9927167bb84cac9cf56f350bee5aae",
+            "max": 1,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ff830930e9e04bdaa73f57e4eafe1979",
+            "value": 1
+          }
+        },
+        "5b515a9e88074259b1067880ad7aa637": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5b72a50beccd472399740c67d5b8a775": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5be79748747e48dc9557e635185b09b7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5c6c3811d9e04247abd52e0f835b6a5e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5c9eb0211674488bbe8ec74c68a6e9a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5cc9c7f2db1846b6905452d7a9568919": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_507d4fec2b8847d79a884853b4d81dad",
+            "max": 3,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ef6284ce29684d8b9b16875076cd579f",
+            "value": 3
+          }
+        },
+        "5cf9cf4d06af477aaadf2c2eafb21a0f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5d99e7c78ae54a2fa6824cfe36498ab4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_6eec510e0a3844dfb7c7bcb3a6b9d910",
+              "IPY_MODEL_dcbf40b9f3d04a29abb5b82cc4f4f43a",
+              "IPY_MODEL_03a5186fafe7424c896a5c8f4b356098"
+            ],
+            "layout": "IPY_MODEL_0c9bb2443ecf460a876558b547c3b97f"
+          }
+        },
+        "5e592f3705ce411dbfccc726d2348933": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_749592c5ae004de4a5f31bab3c2d31f3",
+              "IPY_MODEL_548572561a0045b485ef9dde63326446",
+              "IPY_MODEL_674e652801844a33ba01395ebdb40263"
+            ],
+            "layout": "IPY_MODEL_d06409a05ec640f9a6a87a8925dd23c1"
+          }
+        },
+        "5ec271f8377a43878a090aaecdde01e6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "5f177c38708d4492909da4b8ae0a4120": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "5f3800af43c84d3596987e49afd4961d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_aaa6238192004463834b5ee1b3464cff",
+            "placeholder": "​",
+            "style": "IPY_MODEL_299e59499eda4a1db01880e4fb1d5cd2",
+            "value": " 100/100 [01:25&lt;00:00,  1.18it/s]"
+          }
+        },
+        "5f71880b66d1458e923cc893a88f91bf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6016947c02af4021851e950c72479029": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "61223d9e086a42ab94927964a4455894": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "617aea856f93495d9f56dfc83a33d4bb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "618716c2a7dc4557873d08a9ea2b0b22": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "61c95b7243604620a9151ce8b6fcc910": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d68dcd34129d4922b23a3bc96739814f",
+            "max": 518,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_2e682e41d92343b792991eaa2b72d7de",
+            "value": 518
+          }
+        },
+        "62bad7effcf24059b293404071b83263": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9b6856e1b63c46b78a50bee3336577e7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9cc8e3acf3d74f9796353f621fb6dfbf",
+            "value": " 100/100 [01:21&lt;00:00,  1.22it/s]"
+          }
+        },
+        "632cbce9ea2f4cc5a87028463a877a5c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "6340e0aa27c04db0b48448513e9875c4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "6394dfa7856b4bf49a9325f22dfe1cc1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_95594c0d3f7d4aafb3f61b21b823b32f",
+            "max": 490224630,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_effb0f0cff3c4cc6a8321d0c411a86f6",
+            "value": 490224630
+          }
+        },
+        "6412ab45ef6c45fd88462f76731675f9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "646592d608724342ad765c7e7457740d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2472d601c42041e6acb51d19de547a0a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_59585c4440a64e1fb76601df8aee255d",
+            "value": "Downloading (…)lve/main/config.json: 100%"
+          }
+        },
+        "648f377c77da4818b1817ab95677d5bc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "64f05915a7b040f9a73dfba9e02d249d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "65277dbddbb34381b788a0ee526a0245": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": "100%"
+          }
+        },
+        "663d883b5cbf4a6998db3319c55ee3d8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "67446ba01e9c4922b041e4ef36ff8774": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_33a65dc99580418cb494e29ae5a0fb9a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c419e4cb99994a5bb0cbccca9c0bc5c6",
+            "value": " 444M/444M [00:06&lt;00:00, 69.3MB/s]"
+          }
+        },
+        "674e652801844a33ba01395ebdb40263": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_835bd092bfb64a47b104d20092d61a14",
+            "placeholder": "​",
+            "style": "IPY_MODEL_91d8224cea5940bb9858f43b42869729",
+            "value": " 27.0/27.0 [00:00&lt;00:00, 1.73kB/s]"
+          }
+        },
+        "674feecda5844fc8b669e8153a982b3f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_9ed0a46f8705464f81f2c8e1a4b8cc89",
+              "IPY_MODEL_0f6e284513e94a3f8681d4b4e39fcb54",
+              "IPY_MODEL_7208cb24790c447aae18746d11b7cc7e"
+            ],
+            "layout": "IPY_MODEL_c1fe650a41b14253b0c398f09293310c"
+          }
+        },
+        "67b22ef1c41541dd99fc2b8d445513d2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_484fac29339449d58309c92dbbbd2af2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d216a5de8270482b90d297cf31a09d35",
+            "value": " 1/1 [01:03&lt;00:00, 63.09s/it]"
+          }
+        },
+        "690c1c1fdb98452ea766955c7a4966be": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "699755e8ae9840f0a87246bd89608f67": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_1e6e26bf5f3e4322b0f9ff4352976adb",
+              "IPY_MODEL_b38da01ce29b4009bf824a779d4cafe7",
+              "IPY_MODEL_5f3800af43c84d3596987e49afd4961d"
+            ],
+            "layout": "IPY_MODEL_d34ff744caf646e88cb0606d7a6de704"
+          }
+        },
+        "69f55ea05abe4ca9b21135169edc7a71": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6a3d2f0a94ea4f72bc81400880f8c430": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6a63b2bbe3f34bc6b9a4258a04ca9104": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9f546de07edf4386ae8ef9394eb6c692",
+            "max": 809404185,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_3350308cf34f4c02bd89f6e2a345ed12",
+            "value": 809404185
+          }
+        },
+        "6a6be6466e6a4814870c38d55279e1c1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6c9cca8ae41441b29f2dd7ac81cd35d4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6ce260c95cfa4736a22d77f5faba3888": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6d146fd4003e47978a253192463dd514": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9525813936a14ac49a7ca525a411c2f9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_6a6be6466e6a4814870c38d55279e1c1",
+            "value": "Downloading (…)&quot;pytorch_model.bin&quot;;: 100%"
+          }
+        },
+        "6d34020216d74b588708e9c9f33f800b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6d6241a0e8544b03bd406739bd2e3914": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "6d669ab16e374f0faa089a183bd52532": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6dd394d212694b969b540123f515957a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "6eec510e0a3844dfb7c7bcb3a6b9d910": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_e797e849c5e0443e84af5c12061589d4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_422523d56ec74035b0a55b9c97d1ed19",
+            "value": "Downloading: 100%"
+          }
+        },
+        "6fcd1c300caa489dadeaa50c6c814a14": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "6fe01f5548f947d2aebc95273a592581": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_20eb3303eb2b429891247566f52218c0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_25721e39542d43029d26ac34b4af6d89",
+            "value": "Upload 1 LFS files: 100%"
+          }
+        },
+        "6ff5e86e93914a9ab2ac20d2a32a206e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_330b85404fe84761a72a8cbfb696eae1",
+            "max": 242080800,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_8030efae633f4b018e7863f46267e575",
+            "value": 242080800
+          }
+        },
+        "7171afc8b8dd4e64966065b7f39f2dd6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_6fe01f5548f947d2aebc95273a592581",
+              "IPY_MODEL_c2f3547e877a4f2dac7a1130e6f9acab",
+              "IPY_MODEL_67b22ef1c41541dd99fc2b8d445513d2"
+            ],
+            "layout": "IPY_MODEL_9bbc7693c651492f843088817a65497f"
+          }
+        },
+        "7208cb24790c447aae18746d11b7cc7e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0755ff4ddf1c453f8f6ca501001fc486",
+            "placeholder": "​",
+            "style": "IPY_MODEL_43d49626f9284b23b3bca84aaf9f4616",
+            "value": " 100/100 [02:47&lt;00:00,  1.43s/it]"
+          }
+        },
+        "72254d54d49a4054b49882200eecc49b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "722dd7a1bb984a22ad1b4da14741d7fd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "72e608fe672b40c99de89ad5ce1e33c0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_144c2d74865e41c19a4a6efb4b120ca9",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e8dba2b5fdc94b5598e6ab9f75671cbb",
+            "value": 100
+          }
+        },
+        "73094daa6d4c4bbf93bd29b8c0253e09": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "731ee8128e584ddcbe117dd03612467d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7372f1fa693345ad8f26f0148b2f527b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "74478f6d2baf47999e56952b01ba938f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fe0bc6d3aa0b4d88a63aa611af3bf65d",
+            "placeholder": "​",
+            "style": "IPY_MODEL_73094daa6d4c4bbf93bd29b8c0253e09",
+            "value": "Epoch 3:  37%"
+          }
+        },
+        "745bf50f671a44bc9abddcc6efb736ee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2aa84a0d65254ef49ee100f66e393ae9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_87a1b92e248549a5b9b9833d52e85c76",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "749592c5ae004de4a5f31bab3c2d31f3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fe66b6883afa471eb687430534bd0820",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2b8a201c62c241a89625630f550f6c02",
+            "value": "Downloading readme: 100%"
+          }
+        },
+        "74cbba5d476540188be2501bf934b5cd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "75469c205b314779aef9d1e7ff2fd612": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "75a3f953de714650a03ad3b2319f8a82": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "75e8cbe174904f91b3a9ee3f4572625b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "76839f93896d43dabcb10f14b031c037": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "791025ac27604718a24542401ab225e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7939062da2ee4ebabadb0a5f06ee3276": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "7982ba1cd95e4347ad3fca29f38d0638": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3c7e904af22f42dca56b6421d35412ff",
+            "placeholder": "​",
+            "style": "IPY_MODEL_efb2989e68d844bb875fbdbd5c79d780",
+            "value": "Generating validation split: 100%"
+          }
+        },
+        "79c3843d7f6045799cfc76b2bc4f0837": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_81ae284f0d064843be6279936fba8a13",
+            "placeholder": "​",
+            "style": "IPY_MODEL_1e25f97059cf482587bc1dcb055d4f7c",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "7a20309eef57435f9f35082d5285f444": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6d34020216d74b588708e9c9f33f800b",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b0ee851984d9431597446f79d656d64a",
+            "value": " 1.52k/1.52k [00:00&lt;00:00, 22.3kB/s]"
+          }
+        },
+        "7a2a38deff05410b92c7f0aca5e2f906": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7b2f94dc358c4e5cb6662463e771bb2d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7b6f963d98df4d36b01e21a89fafd957": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7d99b26699f0438ea804db1871d2a172",
+            "placeholder": "​",
+            "style": "IPY_MODEL_791025ac27604718a24542401ab225e2",
+            "value": "Downloading: 100%"
+          }
+        },
+        "7b93f73af3274920ab2b51418e95cff6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7bd828ddfe814d05a62736a9d91a8272": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d3ff6bc3da3b4754af245dcbacd0914c",
+            "max": 71,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_87407d9ae1f54c3c8383e2934aef15b4",
+            "value": 71
+          }
+        },
+        "7c8f64cb9eda44eca40a6ef5a203afc0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7d207f93b4a24696abf379bcc01723dc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7d77a9f92e984ac7b9350addc57cb577": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7d99b26699f0438ea804db1871d2a172": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "7ddc094c928a4b87a7d5895dc558b15b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "7de626274586484c966e3fcd322559af": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_202cb4369e4845a6a60408400f88b0ed",
+            "max": 4021706,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_92c719b392564d339ff73ccc83c966d0",
+            "value": 4021706
+          }
+        },
+        "7df7c889e4794145ba5b20177df36189": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f387bdb0ba094db2892ed92e786886f6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_1510960e07b742c4b1d838b2d533439b",
+            "value": "Downloading: 100%"
+          }
+        },
+        "7ec029d2493f40649921347adbb03ae7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8030efae633f4b018e7863f46267e575": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "80cc4498465e4fecba040320c9bf1af6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_25296141a79c4477aac6635dd30a80e5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_2ee2d4a8635f45dba573b749244f9e2a",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "81255865450c47ea8a9de6b7996514a3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "81ae284f0d064843be6279936fba8a13": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8206f8f3de1a4907ae54d474d422633f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_3880476d3f0e4962be29180763486deb",
+              "IPY_MODEL_ce88d1d6c0494245b812ae65ea2654ad",
+              "IPY_MODEL_18f20450f84d48d7839bb3c676cb53d4"
+            ],
+            "layout": "IPY_MODEL_4619abf6125240f7862c7583a6f68af1"
+          }
+        },
+        "821ebf47157741ae9045004304e1d66d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0ce302531a69423aa36a39e0502f7970",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d80a188b254f4bd1be7b3c18442547ea",
+            "value": " 57/100 [00:46&lt;00:34,  1.24it/s]"
+          }
+        },
+        "8249f31d416e4ed388233cd633c212a7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_18db9e56c0354600851d762c8de0f774",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a524d30afbdc4574be77a664888d32e6",
+            "value": " 100/100 [01:05&lt;00:00,  1.53it/s]"
+          }
+        },
+        "8299c1ef69414603a1604699c777e1f4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "82e30cf225894092a6be203ae026b742": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2e8a6bd2ef104b32868443ac711c88b6",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0e590d1bb05d4bfaa6c0c41cb41e4794",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "82f65ddff78c4c528169704a78d6d9f5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4f2be832c1f04902af8bfc4f5d971057",
+            "placeholder": "​",
+            "style": "IPY_MODEL_dda5061d7d3d4a2cb166bb9473dc3fbb",
+            "value": "Downloading (…)in/added_tokens.json: 100%"
+          }
+        },
+        "835bd092bfb64a47b104d20092d61a14": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "840a81ea307a4633bfd9846f89121257": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8473ba1cc0d44bba85462cdbf12e9514": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "848f3079a55c475f91f8efd0f02d72e3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_1b07db1c1be94ffe98ca2e23ca97e187",
+              "IPY_MODEL_9f4c3f2e2b17443b9f104bf7e1bc80ea",
+              "IPY_MODEL_67446ba01e9c4922b041e4ef36ff8774"
+            ],
+            "layout": "IPY_MODEL_5253bf28cfe948fd8520b5aefd5cdeff"
+          }
+        },
+        "84a6704158ab4806a23226678b1be9a8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_7b6f963d98df4d36b01e21a89fafd957",
+              "IPY_MODEL_19026bb7f79446bc970e1210cccf206f",
+              "IPY_MODEL_e45b9b8af30042d0a0f91ef4ec1aad76"
+            ],
+            "layout": "IPY_MODEL_3735eff345c9459a986b52ac7c469a33"
+          }
+        },
+        "8544e6360d83437cb03e028051e96be4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "86a4453fe0d7495aafe95e8f68f7a44c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "86b758931e9b4f6c81b2b5d61bb0ed86": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3475f0d8415b4f3ba6b5ad701c365e61",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_bb1ee26e35f04a429d3df1f7273b4603",
+            "value": 100
+          }
+        },
+        "873c26ebd5a0403885933700f87ae39f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3ca24d66c54b42868c814abb11d4214e",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_0fe66bd8c6314fdb86ea236d9638f538",
+            "value": 100
+          }
+        },
+        "87407d9ae1f54c3c8383e2934aef15b4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "87a1b92e248549a5b9b9833d52e85c76": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8a3af3818f69463f845e95c933ac00cd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_b968d28f243543b29cf0733e2d9fc516",
+              "IPY_MODEL_e0f0d44a4e834e9291b2c021fcb1dad9",
+              "IPY_MODEL_e0732c157cbf446f80cd1b4d52f7f6b8"
+            ],
+            "layout": "IPY_MODEL_259d3cba0a5b4943b4b025f921edf06b"
+          }
+        },
+        "8ad84d92e3f2470084c072e64a46cfb3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8b00742b502d493094ad605fc90b5b09": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8b4f59bf71c64c2293a9e089b963b914": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8c3fc7e7b9354d0fb59602100bc5ab1f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "8cef8071dc984acc8a003134e8d64a11": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8d98ed226dd1489e83099782d51d7b55": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8eda879a6d224fb091f538c2806d7890": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8eef683c23a14e9ca9cc8e260a8d25aa": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "8f12f7c6ea604de7ab155971ffea8275": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "8f29c28a5f154fcfb6cb2f382eb1e1b1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": "100%"
+          }
+        },
+        "8f6e8799b4e1454ea04bb9c94b70fdb8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a999d2c30b9644a7967b7109c3aae629",
+            "placeholder": "​",
+            "style": "IPY_MODEL_08c07275cbbe4fd0822c354d99c303ea",
+            "value": " 100/100 [01:20&lt;00:00,  1.24it/s]"
+          }
+        },
+        "90761ecf88ad4a1c8dc190928b48fdba": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_f51518a3bf3b4a7582dbe26fca21ca6e",
+              "IPY_MODEL_09c44c23e97c4293bc1d30f234634c42",
+              "IPY_MODEL_561abfbe2ed9405d8bc9c67f3a4c4c8a"
+            ],
+            "layout": "IPY_MODEL_c44ea4249c324b7cbbb69798e034cb85"
+          }
+        },
+        "90d6691af3fd49899b196ff7337d71b3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "91d8224cea5940bb9858f43b42869729": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "91f16cb20b2d4590ab22a4b964290569": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_82e30cf225894092a6be203ae026b742",
+              "IPY_MODEL_4a987dc4a0e54e5da442be8d6a1c7f09",
+              "IPY_MODEL_cd21d646227b4d478abb70ba04588215"
+            ],
+            "layout": "IPY_MODEL_01b01e7329334686ba39c11ec18e9df5"
+          }
+        },
+        "92c719b392564d339ff73ccc83c966d0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "92f74f940eb74ceb89139e25dc1fe869": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_caf81cab2e1c45c38007dc88bc9a9e0e",
+            "placeholder": "​",
+            "style": "IPY_MODEL_b30a4626320c4e78b3a033cf257946fe",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "932854c5974142b3b906ac1db17725fc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "938da511fca04f77af54fe3b34287e6c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9460488365d343e887fb88aafc4c434b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4cacd92cb1f04dcea344f93e816d6244",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fd4d064de57d469c977318add3069303",
+            "value": " 362/362 [00:00&lt;00:00, 8.92kB/s]"
+          }
+        },
+        "9479170c55a34e5a9ccce3115f01b68e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9525813936a14ac49a7ca525a411c2f9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "95594c0d3f7d4aafb3f61b21b823b32f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "95ec17f083be45d1a48d643e62f4dbf8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "96b45a24defe461998123ec31aba1d97": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "971fb37793b04b02916266e0606a8cd3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9e5391e58b654a54af53ca6b156d4027",
+            "max": 1,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_a772a8f8485b4cbc954363c5d25a1355",
+            "value": 0
+          }
+        },
+        "97e80dbb785548e0ad4b7724e91a27f7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9812cfa5ccd14b7aa756a383c793c2c5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7ec029d2493f40649921347adbb03ae7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c922e749c8464d2f9080b3bd2333d04f",
+            "value": " 809M/809M [01:03&lt;00:00, 14.0MB/s]"
+          }
+        },
+        "986ff3190ef14c5c907d83383571f267": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f59a9d0b14c348d6b9c221744c256afc",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4fefc71218894bd4a6b2e95ff3a882e5",
+            "value": " 242M/242M [00:03&lt;00:00, 65.5MB/s]"
+          }
+        },
+        "98c6ca051cde41cf806b1b8bd9caf6c9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "99bcc899c1d54ea6b6a95fdda3d4e54f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cbf0235e60724033a400c2cb38b3971a",
+            "max": 1048,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_90d6691af3fd49899b196ff7337d71b3",
+            "value": 1048
+          }
+        },
+        "9a45e993bffc469a8a156cba70774d25": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_82f65ddff78c4c528169704a78d6d9f5",
+              "IPY_MODEL_7bd828ddfe814d05a62736a9d91a8272",
+              "IPY_MODEL_9da3a58c74e64d4d8e39921e472fb6ea"
+            ],
+            "layout": "IPY_MODEL_c253f1450fdc49939ad663b6f98b6929"
+          }
+        },
+        "9a7cb4d7e9514575a93e2f86fc32fb4b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "9aaff87ef6bf4f71b67dc13553aa73b2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9ab3a07b87854294b687ab1bd1ce2fe1": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_45c29055f8a74361b562fb2baaa3b71f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_731ee8128e584ddcbe117dd03612467d",
+            "value": "Downloading (…)okenizer_config.json: 100%"
+          }
+        },
+        "9b045fecb5c24541b6611ba71237f6f7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "9b0fe2691d7041fe8841d87beed2bf7b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_f0d43f6407674c12b85a6292284b4ba4",
+              "IPY_MODEL_99bcc899c1d54ea6b6a95fdda3d4e54f",
+              "IPY_MODEL_9c138abac1894ebebb334b8044ee6ca9"
+            ],
+            "layout": "IPY_MODEL_26bb592b09c94ba081cd1f913c318f73"
+          }
+        },
+        "9b6856e1b63c46b78a50bee3336577e7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9bbc7693c651492f843088817a65497f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9bce140411404cad931ec4022a76989e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_50ce7fc092624343a610286377ecd39a",
+              "IPY_MODEL_b28110567ad04fdeafea8f405f71e7ef",
+              "IPY_MODEL_f578278adfb146e8bdf89810a39d43cb"
+            ],
+            "layout": "IPY_MODEL_fbed03f8b8ad47638a418b9f423e4c26"
+          }
+        },
+        "9c081ba4b4b7409caef98b8c7754c9b6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9c138abac1894ebebb334b8044ee6ca9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9aaff87ef6bf4f71b67dc13553aa73b2",
+            "placeholder": "​",
+            "style": "IPY_MODEL_4ebee50caff240aea9377fa4a2d0d7cf",
+            "value": " 1.05k/1.05k [00:00&lt;00:00, 41.0kB/s]"
+          }
+        },
+        "9cc8e3acf3d74f9796353f621fb6dfbf": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9d0bb9e6cae5452a8f7909340d0ab21c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "9da3a58c74e64d4d8e39921e472fb6ea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_617aea856f93495d9f56dfc83a33d4bb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_23e4cf09102a4753844ceed08a211d53",
+            "value": " 71.0/71.0 [00:00&lt;00:00, 4.02kB/s]"
+          }
+        },
+        "9db7c2d529ea46d48e22271d8432f137": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "9dcbe88c6ba446ea9584331776d2748a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "9dde5575c8e7438fa2d86e4b9a4fb33f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_16ea181fc8694d29b499b46678fbdaf3",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e6b5096cac864d27ad88010c2180db29",
+            "value": " 809M/809M [01:03&lt;00:00, 14.1MB/s]"
+          }
+        },
+        "9e5391e58b654a54af53ca6b156d4027": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": "20px"
+          }
+        },
+        "9e5bbac1661d4385b06a3caa40cfce63": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a867c537beb34cdf905e80246d31dd97",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ab41966250404933aea9736461583520",
+            "value": " 100/100 [00:00&lt;00:00, 124.87 examples/s]"
+          }
+        },
+        "9ea85c5be7104fdbb67f52414ba1a1bd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "9ed0a46f8705464f81f2c8e1a4b8cc89": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a105133b82344a97b79250d8cde50f74",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c474aabdf84b459aae6c9c0de4526b47",
+            "value": "100%"
+          }
+        },
+        "9ef9d3b7c4e141c99299d21e270347af": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "9f4c3f2e2b17443b9f104bf7e1bc80ea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d75985c018114da8943c9bad0c61869b",
+            "max": 443802181,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_fc88c486f35747cd8a3e0eeaf67ebfb6",
+            "value": 443802181
+          }
+        },
+        "9f546de07edf4386ae8ef9394eb6c692": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a071ed8d726f45b4a07251b60793dc6a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a105133b82344a97b79250d8cde50f74": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a27fc920f8c94953a0c3e9b2120f1b86": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a35f8906c1ae46828120319694065815": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1c1855ade6204625bfaab54ca2159af5",
+            "placeholder": "​",
+            "style": "IPY_MODEL_210766df14774c1e89d0df73f294daa6",
+            "value": " 100/100 [01:21&lt;00:00,  1.22it/s]"
+          }
+        },
+        "a4dc6daaa87e4a4689ffc623b0a3b259": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_97e80dbb785548e0ad4b7724e91a27f7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_20e0bf2b09d841d6bc9e1f36ec4079bc",
+            "value": "pytorch_model.bin: 100%"
+          }
+        },
+        "a4ddea7815394732a0125128fcd9e1f2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c2a0bcc5ca8e42439ef2e153193714be",
+            "placeholder": "​",
+            "style": "IPY_MODEL_dd4114a8f79b4725951e78ab4f31d19b",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "a4eacb994f2147d29d2d68e9b3c456aa": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a524d30afbdc4574be77a664888d32e6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a535138c7cfc454e8a096f31b4625331": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_745bf50f671a44bc9abddcc6efb736ee",
+              "IPY_MODEL_07b75ae72a6a4d16a3ff73a1debe2ee5",
+              "IPY_MODEL_082d0b472b90409f8ab9b02391df63a4"
+            ],
+            "layout": "IPY_MODEL_1c2bd9e72e334917b3ce39810bf5ea0b"
+          }
+        },
+        "a772a8f8485b4cbc954363c5d25a1355": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "a7f7c95743214d17a1cd103c2add1b3c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "a7fb70b9171c4958bc5f5c37e51f8cd6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a867c537beb34cdf905e80246d31dd97": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a999d2c30b9644a7967b7109c3aae629": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "a9ed7db85a364e6384f84f216080d24a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "aaa6238192004463834b5ee1b3464cff": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "aad2e43eeafa4cccb5e476d3fce4dacb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ab1569f009a54b018f8e1d90a51172ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_d2d0f66f84874e679594bc856182c6c2",
+              "IPY_MODEL_e5562397a34348be901b498203690a42",
+              "IPY_MODEL_cfdf85f797074bc8af900f5623b63e67"
+            ],
+            "layout": "IPY_MODEL_ee26b20d24b94233b242a490bbb528bd"
+          }
+        },
+        "ab1c3ba6663a40c383a57333f5b13ddb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3612afa317c5414bbffdbc1f241eb133",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ca6747f101dc44fa8d3b85f668fff5ed",
+            "value": "Downloading (…)/main/tokenizer.json: 100%"
+          }
+        },
+        "ab41966250404933aea9736461583520": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ab6b00b5c38d40e4878e5de67bba6b95": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_262f11dfba44467c882893cec6523189",
+            "placeholder": "​",
+            "style": "IPY_MODEL_3e8e09b6655a4c8fb3995915a69c795f",
+            "value": " 362/362 [00:00&lt;00:00, 16.7kB/s]"
+          }
+        },
+        "abd398c4b93343a49f7882d3b141ccf4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7c8f64cb9eda44eca40a6ef5a203afc0",
+            "placeholder": "​",
+            "style": "IPY_MODEL_10aad821076a43b88b833f52d41df0ef",
+            "value": " 809M/809M [00:19&lt;00:00, 43.4MB/s]"
+          }
+        },
+        "ac08a565f2d5447a95d2e6af307f3f09": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ac96d471b96049c4aace63a7d88ec166": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "acb18d163a98436abc6a34c80d0b9875": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "acfeebabb13647ddbbe4372e192b235a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ad251dd399bf4671978561773be7da7a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_1d3f96ad71b74c31b18b50d0dafefb6e",
+              "IPY_MODEL_6ff5e86e93914a9ab2ac20d2a32a206e",
+              "IPY_MODEL_986ff3190ef14c5c907d83383571f267"
+            ],
+            "layout": "IPY_MODEL_4c06e9c680b6471c8305042a7e3757e3"
+          }
+        },
+        "ad391511f2ec4e3ebb69865afee7ae6b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_9479170c55a34e5a9ccce3115f01b68e",
+            "max": 1296245,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_0fedf481a76a4d319ddc6afe51345a36",
+            "value": 1296245
+          }
+        },
+        "ae1f8706e72943989d91f9a44a40eeeb": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ae8b189059e94a7ab73fb256432c18df": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_0098775e311344f681335445edadd72f",
+            "max": 455555434,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_632cbce9ea2f4cc5a87028463a877a5c",
+            "value": 455555434
+          }
+        },
+        "aeccbc9b9c3e4038874656c34f12d9f4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "aef15ac1c7214177b7a890917b2a350d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "aff4e5ac7e384d408fc23ca0a8d3658f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "b0095f1cb2364fc991f05f312656947f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b02d03f2ac8d47559d03eb83a01d467e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b04b0c322c624afa8bb5a128b2af08b6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b0ab92d005974b959f7cb0f2cb9b11d6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b0ee851984d9431597446f79d656d64a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b12a725c43db4fa4ad13d82c75738994": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_74cbba5d476540188be2501bf934b5cd",
+            "placeholder": "​",
+            "style": "IPY_MODEL_c08394b19b98474798fc290bc540ddd5",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "b132e3a6f07e452382eadbedff054b94": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bd0e4a5ac7b5440a8b403a36fdaae181",
+            "placeholder": "​",
+            "style": "IPY_MODEL_fd3d2e91c7a64c2782727d2c29020fbc",
+            "value": "Generating train split: 100%"
+          }
+        },
+        "b28110567ad04fdeafea8f405f71e7ef": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_690c1c1fdb98452ea766955c7a4966be",
+            "max": 355,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_c08e405d7915496089723b6d5e78d163",
+            "value": 355
+          }
+        },
+        "b294221a318349228f631ca89407740b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ae1f8706e72943989d91f9a44a40eeeb",
+            "max": 1,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_bc7bb44709434398a99c395a01d2b3b6",
+            "value": 1
+          }
+        },
+        "b2f81adfc7624d0ebec30a6f49d3b0d3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "b30a4626320c4e78b3a033cf257946fe": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b38da01ce29b4009bf824a779d4cafe7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bb888b3abe26402897177229c0a6ab01",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_009ae1d114cb48d0990e934e19ee961f",
+            "value": 100
+          }
+        },
+        "b3a98298b4ea434da0d8815ba0f2c4a4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b3d5b8a11f8948d0bb7273e036841869": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "b49ab085f6e04c7398e90e09eda48c5a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "b4afe9af86d1487cbe0cb9f4956db2e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a27fc920f8c94953a0c3e9b2120f1b86",
+            "max": 809400699,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_722dd7a1bb984a22ad1b4da14741d7fd",
+            "value": 809400699
+          }
+        },
+        "b50f6068222b4b7d9c8a865bd41ce277": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ca44a4c94aea499ea738f536eacf4b9b",
+              "IPY_MODEL_582d8cd7787443f59398e2f79c328b51",
+              "IPY_MODEL_821ebf47157741ae9045004304e1d66d"
+            ],
+            "layout": "IPY_MODEL_8f29c28a5f154fcfb6cb2f382eb1e1b1"
+          }
+        },
+        "b6168e1cb7354844a2ac17dee7a31168": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d22010093bc54928b96389c8cc48d409",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_148b60b8a9a44244874d2db13de48a00",
+            "value": 100
+          }
+        },
+        "b64f8b95e23c4baf87fcec7fb16aedfa": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b71da8215fd74394aeef7b2835ebdce2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "b760aaf9ca3047378404f446549355ef": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "b968d28f243543b29cf0733e2d9fc516": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_4d6704d874404c9996e32b16b7773169",
+            "placeholder": "​",
+            "style": "IPY_MODEL_0c44b50f550a42d5a89d35c0233fa0bb",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "b9b02352a20e45ac8128f58b9387435d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_07054014fd004b44993a392856f25f58",
+              "IPY_MODEL_b4afe9af86d1487cbe0cb9f4956db2e2",
+              "IPY_MODEL_abd398c4b93343a49f7882d3b141ccf4"
+            ],
+            "layout": "IPY_MODEL_3fda98dab7574ba489090143ce8a0e82"
+          }
+        },
+        "ba402e291fd94f8ab8f1a74c5c1ac551": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ba77336ed8a64ce1b7b3a561844b53ef": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ee9f3bdcf3814bbbac4e053b4c169704",
+            "placeholder": "​",
+            "style": "IPY_MODEL_cebe7c4bb7e447949431cf58deedef30",
+            "value": "Generating test split: 100%"
+          }
+        },
+        "baa432ed76ae437e8946ebe41301453c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1df30bb3175541a7b7a6541b38d51b89",
+            "placeholder": "​",
+            "style": "IPY_MODEL_e563fc2ca1ef4b668604bea1c50674e2",
+            "value": " 490M/490M [00:07&lt;00:00, 80.9MB/s]"
+          }
+        },
+        "baad5e47bfc940229c7c19cb8372b59c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "bb1ee26e35f04a429d3df1f7273b4603": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "bb888b3abe26402897177229c0a6ab01": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bc7bb44709434398a99c395a01d2b3b6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "bcaced45f306473887ab7c07df871481": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "bcb3bc46a920467d8441c8fe2c0081f7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bd0e4a5ac7b5440a8b403a36fdaae181": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "be37899db94d4c15b8e194c03b057a45": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bf2d692c9fd24236a6a760a293cb5a13": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": null
+          }
+        },
+        "bf3538bb8a33408088307bb3dba05a14": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bf9d9715e7684c4e8ac29cbcabf1c600": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bfc5138baadf4385a0ed6b87107fabec": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "bfc6976f3a4b4de3bd42aa1dc9ab73e5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "c08394b19b98474798fc290bc540ddd5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c08e405d7915496089723b6d5e78d163": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c0c9ce38c68446ddad343c8abc4aa3a9": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c0cf700f7872458385250ba075a8edb1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c1f64aaadd484bb2900aaebadeb305d5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c1fe650a41b14253b0c398f09293310c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c21173370f63409b84b9f40abc202efd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2781fb98daf147638db891d565d2f194",
+            "placeholder": "​",
+            "style": "IPY_MODEL_da910c9d7bc94d6fabe99bfcd626d9a2",
+            "value": "Downloading (…)rocessor_config.json: 100%"
+          }
+        },
+        "c253f1450fdc49939ad663b6f98b6929": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c2a0bcc5ca8e42439ef2e153193714be": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c2f3547e877a4f2dac7a1130e6f9acab": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_aef15ac1c7214177b7a890917b2a350d",
+            "max": 1,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_75e8cbe174904f91b3a9ee3f4572625b",
+            "value": 1
+          }
+        },
+        "c34474a8f453410f8f3dc39c835e3a2d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c3735a62d26743cc88f0bb71712edaa2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c3f54d242da14b689f6e213867b81cec": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c419e4cb99994a5bb0cbccca9c0bc5c6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c44ea4249c324b7cbbb69798e034cb85": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c46ec088b99646f091f934536af46d5e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2a459b1c958240d89f753fe695b457e0",
+            "max": 4742,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_7939062da2ee4ebabadb0a5f06ee3276",
+            "value": 4742
+          }
+        },
+        "c474aabdf84b459aae6c9c0de4526b47": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c5083eb93376434e9a53fc44d7d215b9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_394b5ca6361e4d38ba6cca638de5cdcb",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7b2f94dc358c4e5cb6662463e771bb2d",
+            "value": " 1.30M/1.30M [00:00&lt;00:00, 24.7MB/s]"
+          }
+        },
+        "c5810b986d064e93ac00ff911d3d09de": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0d5904889d6246e4b0bd8223d9ce79ab",
+              "IPY_MODEL_09e57cfef8d04198b07337e6adfd3cfd",
+              "IPY_MODEL_9460488365d343e887fb88aafc4c434b"
+            ],
+            "layout": "IPY_MODEL_8ad84d92e3f2470084c072e64a46cfb3"
+          }
+        },
+        "c5d372a9962c49ada49b96a66c5ecd7e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "c5f481bd341a48668518912efbd6a35a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c5f9fb53d093461282bc9ebd4a68ead4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c61132d2ccbb404ea969d7701fbc3ed7": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_1355cef1e865410182443c3b8ba73fd2",
+            "max": 3,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ef4bc97031ee4e798ec0ccb3c1b76e2c",
+            "value": 3
+          }
+        },
+        "c65a6cc99b06467cbc7f4efe8d80aae0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c663b10ffce1432c89a3948e324571b0": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c6656f51d29747c7a831f8b4739b8cd7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c6e2d6abd785494ca143b5978811c326": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "c6e7bfb4e3144b16bcfd3fd12673d853": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c75e6f8363fc4bd1ab7d1c6513f60dd5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_56c8c883282e4f74ae1c353455136380",
+              "IPY_MODEL_e13b3d868fe3450cac508a8799743696",
+              "IPY_MODEL_3a1168d83bbd44c887b93d20f8eb59a6"
+            ],
+            "layout": "IPY_MODEL_64f05915a7b040f9a73dfba9e02d249d"
+          }
+        },
+        "c8d62278ed494aa1948d4ddac0b5e94c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c922e749c8464d2f9080b3bd2333d04f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "c97025e7d015445fafa406c4c1a89af7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "c99fc92b5c87414faa6bafd1d91ce9c4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_dd41ea80146343bcbee92bed78324879",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_04b01b03fcc143fa8633b52ec231f026",
+            "value": 100
+          }
+        },
+        "ca44a4c94aea499ea738f536eacf4b9b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c5f9fb53d093461282bc9ebd4a68ead4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_7ddc094c928a4b87a7d5895dc558b15b",
+            "value": "Validation DataLoader 0:  57%"
+          }
+        },
+        "ca6747f101dc44fa8d3b85f668fff5ed": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ca6fcf9c01fe4f2db382b6b0f8cb169d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ca8a046ed39e45f79234a10f85ed09d4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5b72a50beccd472399740c67d5b8a775",
+            "placeholder": "​",
+            "style": "IPY_MODEL_488139fa453f40e6895a0bac7d5cf840",
+            "value": " 100/100 [01:24&lt;00:00,  1.19it/s]"
+          }
+        },
+        "caf81cab2e1c45c38007dc88bc9a9e0e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cbf0235e60724033a400c2cb38b3971a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cc2651a0102d49c7b6a9ac6e82db8c9a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ccd7cb252ac34be1afa95313cd576555": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "cd21d646227b4d478abb70ba04588215": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_ac96d471b96049c4aace63a7d88ec166",
+            "placeholder": "​",
+            "style": "IPY_MODEL_86a4453fe0d7495aafe95e8f68f7a44c",
+            "value": " 100/100 [01:28&lt;00:00,  1.13it/s]"
+          }
+        },
+        "cd63bf0c96b6466586c66240f67b35a5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_5b515a9e88074259b1067880ad7aa637",
+            "max": 362,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_6dd394d212694b969b540123f515957a",
+            "value": 362
+          }
+        },
+        "cd80b89157374e759c3a24091fced46b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "cdf0d854eba142779798e0ac495c02af": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_297ba8af5a704c5ca34d0f406de3e918",
+            "placeholder": "​",
+            "style": "IPY_MODEL_95ec17f083be45d1a48d643e62f4dbf8",
+            "value": " 100/100 [00:58&lt;00:00,  1.71it/s]"
+          }
+        },
+        "ce88d1d6c0494245b812ae65ea2654ad": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_648f377c77da4818b1817ab95677d5bc",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_ccd7cb252ac34be1afa95313cd576555",
+            "value": 100
+          }
+        },
+        "ce963a069b50408abc6cf6073857c5ee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_21d179e89c8d47768585c9d9d3bd6e20",
+              "IPY_MODEL_f88cf9ec7d8b4faa80017e24f99d5dc8",
+              "IPY_MODEL_7a20309eef57435f9f35082d5285f444"
+            ],
+            "layout": "IPY_MODEL_6d669ab16e374f0faa089a183bd52532"
+          }
+        },
+        "cebe7c4bb7e447949431cf58deedef30": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "cf862b504d86425f886ed6d19b55b05a": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "cfa9b34f74b541fc9c54b905cffa05ad": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "cfdf85f797074bc8af900f5623b63e67": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a071ed8d726f45b4a07251b60793dc6a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5f71880b66d1458e923cc893a88f91bf",
+            "value": " 100/100 [01:25&lt;00:00,  1.17it/s]"
+          }
+        },
+        "d06409a05ec640f9a6a87a8925dd23c1": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d135d783486d456494d15ef2a339ebff": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_74478f6d2baf47999e56952b01ba938f",
+              "IPY_MODEL_24e315cb82a747d6b9566b461db6aee9",
+              "IPY_MODEL_0d2f68be02e7495fab83926f99b93586"
+            ],
+            "layout": "IPY_MODEL_65277dbddbb34381b788a0ee526a0245"
+          }
+        },
+        "d1837ece0226413489f3df0dfd7f3279": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d216a5de8270482b90d297cf31a09d35": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d22010093bc54928b96389c8cc48d409": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d2d0f66f84874e679594bc856182c6c2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_b64f8b95e23c4baf87fcec7fb16aedfa",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f9bf6bbc52ea46bc8204f3756f2f981b",
+            "value": "Validation DataLoader 0: 100%"
+          }
+        },
+        "d34ff744caf646e88cb0606d7a6de704": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "d3995239fdf54fabb7fb42417dd2d1e2": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d3ff6bc3da3b4754af245dcbacd0914c": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d494ec40fa104f16ace482fa5738e771": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ba77336ed8a64ce1b7b3a561844b53ef",
+              "IPY_MODEL_02700c32e4d64a66818ac92209384b14",
+              "IPY_MODEL_9e5bbac1661d4385b06a3caa40cfce63"
+            ],
+            "layout": "IPY_MODEL_bf2d692c9fd24236a6a760a293cb5a13"
+          }
+        },
+        "d510866a711a4f5bb98748690dc89fbe": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d525b6ed32414b8583d8726d83dd747b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "d5667dae1b4d479db3745879a34b9ab5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d56998a0695e434bb7fe3857f5075083": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "d643c6ffb4964990899a47cc02a63b9d": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_04fa08f418e74bfe8d274620cd07e448",
+              "IPY_MODEL_ae8b189059e94a7ab73fb256432c18df",
+              "IPY_MODEL_5915cae6f7ba4d5caa52ff5c8f854b38"
+            ],
+            "layout": "IPY_MODEL_3db9e9823c2d4f418cd6707058ff07ba"
+          }
+        },
+        "d68dcd34129d4922b23a3bc96739814f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d6e90d985e8b4f7fa5d8258c72a8ba9e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_5053663ab6874c378d764dc8584b6aca",
+              "IPY_MODEL_873c26ebd5a0403885933700f87ae39f",
+              "IPY_MODEL_4058a3b2505f441f84f78fe4f7188aa8"
+            ],
+            "layout": "IPY_MODEL_d525b6ed32414b8583d8726d83dd747b"
+          }
+        },
+        "d75985c018114da8943c9bad0c61869b": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "d80a188b254f4bd1be7b3c18442547ea": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "d91e67e21bfa49888bf6316c154bcf77": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": null
+          }
+        },
+        "da517c560a174ed3b3a0d342ab9531d4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_0d29cb058287441397849858958eecc5",
+              "IPY_MODEL_971fb37793b04b02916266e0606a8cd3",
+              "IPY_MODEL_f397c359a4844fe0b43cbd55f7e45e2c"
+            ],
+            "layout": "IPY_MODEL_5be79748747e48dc9557e635185b09b7"
+          }
+        },
+        "da910c9d7bc94d6fabe99bfcd626d9a2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "db3b31f6234f4c0781e02e27c0a78139": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c0c9ce38c68446ddad343c8abc4aa3a9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_a7f7c95743214d17a1cd103c2add1b3c",
+            "value": " 809M/809M [01:03&lt;00:00, 13.5MB/s]"
+          }
+        },
+        "dbe52dd9651f42238a11351f10b22b4a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_3f76ca5381b64731af382a63b890292b",
+              "IPY_MODEL_5af452039cad49ee92c938aaffa25765",
+              "IPY_MODEL_05c1c99b4aff486a9c5eeadf9bd8230a"
+            ],
+            "layout": "IPY_MODEL_167cf75950f6434293f6809a84f998f3"
+          }
+        },
+        "dcaa8093d0194d76871523cd07347bd6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dcbf40b9f3d04a29abb5b82cc4f4f43a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_acfeebabb13647ddbbe4372e192b235a",
+            "max": 489,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_b2f81adfc7624d0ebec30a6f49d3b0d3",
+            "value": 489
+          }
+        },
+        "dd0b6870c8b6435691009ca66fa71b09": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_eee6b3f385774227b35fc4d83eb0171f",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f20da578968f43c3ac44efa032dbd6e2",
+            "value": " 3/3 [01:08&lt;00:00, 22.16s/it]"
+          }
+        },
+        "dd4114a8f79b4725951e78ab4f31d19b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "dd41ea80146343bcbee92bed78324879": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "dda5061d7d3d4a2cb166bb9473dc3fbb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ddd6a6f26e4a40de85db830c02834c4c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_646592d608724342ad765c7e7457740d",
+              "IPY_MODEL_c46ec088b99646f091f934536af46d5e",
+              "IPY_MODEL_3ce6f898ce604f258efab30dd9f65b79"
+            ],
+            "layout": "IPY_MODEL_38fff333701c4678b5c69863aa8992ac"
+          }
+        },
+        "de3f7930ae454905be655bf33f045280": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "def152f1a9e84c7e90e6e24f001f29a2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_140f7d5cb0fb4b4b8598d1552a429052",
+              "IPY_MODEL_ad391511f2ec4e3ebb69865afee7ae6b",
+              "IPY_MODEL_c5083eb93376434e9a53fc44d7d215b9"
+            ],
+            "layout": "IPY_MODEL_56fea1b142db47fbab0b118185587e76"
+          }
+        },
+        "df11ed2a5b2f4264b82cfd95724e7a32": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_dcaa8093d0194d76871523cd07347bd6",
+            "max": 6,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_8544e6360d83437cb03e028051e96be4",
+            "value": 6
+          }
+        },
+        "e05ca35fa13a42e0bfb8daef4706d291": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e0732c157cbf446f80cd1b4d52f7f6b8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_fad67a0d8f834d6eb9609fc0ecec94c8",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9c081ba4b4b7409caef98b8c7754c9b6",
+            "value": " 100/100 [01:55&lt;00:00,  1.16s/it]"
+          }
+        },
+        "e0da7e4a45a846c0ac14269e5bbb77f8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": null
+          }
+        },
+        "e0f0d44a4e834e9291b2c021fcb1dad9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bf3538bb8a33408088307bb3dba05a14",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_24c7acb091ab4037a6b4a2eb8a1085e3",
+            "value": 100
+          }
+        },
+        "e13b3d868fe3450cac508a8799743696": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_2a058b66d21642f3ab38b917a57ead4c",
+            "max": 355,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_0eccda6238eb4756863a6efeeadc9efb",
+            "value": 355
+          }
+        },
+        "e30df53a96fc474da072e8692a0d1d58": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e32e4cee40f14064b9cd93b7688c3ff5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_e82ab023dc0e4a2dbe8da18f1b346ca0",
+              "IPY_MODEL_542c34c7d55c400a8f623232403fe250",
+              "IPY_MODEL_0759cda7bd084b02921689bc5e319ba5"
+            ],
+            "layout": "IPY_MODEL_543c3f05eb0547298950b7e7d8c64467"
+          }
+        },
+        "e347c9815ff64f93884e65d882c8dc64": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_293e17ab3b4a462ba7d4adc2de35aa05",
+            "placeholder": "​",
+            "style": "IPY_MODEL_36c215478b2f415e904a24de4b91d9d7",
+            "value": "Computing checksums: 100%"
+          }
+        },
+        "e45b9b8af30042d0a0f91ef4ec1aad76": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_11e6194ce58c4c05a4cf3c9c55b4acc4",
+            "placeholder": "​",
+            "style": "IPY_MODEL_5f177c38708d4492909da4b8ae0a4120",
+            "value": " 4.90k/4.90k [00:00&lt;00:00, 102kB/s]"
+          }
+        },
+        "e4dd0f4da33c453e886144de5c93aeb3": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e529a78e1aba43d980b2953aef3cdfba": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "e5562397a34348be901b498203690a42": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f3cb306bf10b448ab173861f392ad1d7",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_52cbbbf6bc6643e9b43d844586ab453e",
+            "value": 100
+          }
+        },
+        "e563fc2ca1ef4b668604bea1c50674e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e6523a394c4442bd949cae3f7666b6d4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e6b5096cac864d27ad88010c2180db29": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "e6f8227c5e914a279428bfc620591ef0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_79c3843d7f6045799cfc76b2bc4f0837",
+              "IPY_MODEL_33170adc2cbe4b3daa9073cee501d854",
+              "IPY_MODEL_8f6e8799b4e1454ea04bb9c94b70fdb8"
+            ],
+            "layout": "IPY_MODEL_9ea85c5be7104fdbb67f52414ba1a1bd"
+          }
+        },
+        "e71b1fe193ba49afb42fe50f96663070": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e797e849c5e0443e84af5c12061589d4": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "e82ab023dc0e4a2dbe8da18f1b346ca0": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_f414756091e34756a98d812bcf299f69",
+            "placeholder": "​",
+            "style": "IPY_MODEL_d510866a711a4f5bb98748690dc89fbe",
+            "value": "Upload 1 LFS files: 100%"
+          }
+        },
+        "e8dba2b5fdc94b5598e6ab9f75671cbb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e8f2e16d8a9f4091a2d6438892c731b4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "e9b2a001c8dc4591b00a21893c56dceb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_a9ed7db85a364e6384f84f216080d24a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_98c6ca051cde41cf806b1b8bd9caf6c9",
+            "value": " 1.30M/1.30M [00:00&lt;00:00, 1.15MB/s]"
+          }
+        },
+        "ea0303a1646b454cb26f023c0d8b7804": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_a4dc6daaa87e4a4689ffc623b0a3b259",
+              "IPY_MODEL_24b5e61aecd84402a6261b4b06146559",
+              "IPY_MODEL_db3b31f6234f4c0781e02e27c0a78139"
+            ],
+            "layout": "IPY_MODEL_c1f64aaadd484bb2900aaebadeb305d5"
+          }
+        },
+        "ea7c0bd905074e5d8105bb82036bea1c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3528f8245a2044c4b2037481bdaf39a7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_047bdaa0ff9d4a4f8d6f46fca23bd0d2",
+            "value": " 100/100 [01:20&lt;00:00,  1.24it/s]"
+          }
+        },
+        "eb5f6ef011b44f7d8a62a35ee66899db": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_61223d9e086a42ab94927964a4455894",
+            "placeholder": "​",
+            "style": "IPY_MODEL_aeccbc9b9c3e4038874656c34f12d9f4",
+            "value": "Extracting data files: 100%"
+          }
+        },
+        "ebeb73a097574a8597d3592329674e44": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ec11d0d99c684e2c87c1bf1c05220a95": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ec2fc9e744d9460f9063f9c0aac4c3d5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ed76219299d54f908eff9c9678e1e00f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ed98bdb5c8364a6782a1883411acd5f5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "ee26b20d24b94233b242a490bbb528bd": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": "inline-flex",
+            "flex": null,
+            "flex_flow": "row wrap",
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": "hidden",
+            "width": "100%"
+          }
+        },
+        "ee9eb1bc7197470487cf0dea02a3d8f9": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_a4ddea7815394732a0125128fcd9e1f2",
+              "IPY_MODEL_3da1fd9a348f4c7bb07889c017cc0c2a",
+              "IPY_MODEL_62bad7effcf24059b293404071b83263"
+            ],
+            "layout": "IPY_MODEL_c5d372a9962c49ada49b96a66c5ecd7e"
+          }
+        },
+        "ee9f3bdcf3814bbbac4e053b4c169704": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "eee6b3f385774227b35fc4d83eb0171f": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "ef4bc97031ee4e798ec0ccb3c1b76e2c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "ef6284ce29684d8b9b16875076cd579f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "efb2989e68d844bb875fbdbd5c79d780": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "efbbbb45e1554253bbf331525f219e4c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_ab1c3ba6663a40c383a57333f5b13ddb",
+              "IPY_MODEL_4664a4a1ab034098a12b6ad238c0391b",
+              "IPY_MODEL_257fa5076dd74486b7751bffa39c2ef8"
+            ],
+            "layout": "IPY_MODEL_b02d03f2ac8d47559d03eb83a01d467e"
+          }
+        },
+        "effb0f0cff3c4cc6a8321d0c411a86f6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f09e42ab2e9f4560aa68de42fbc4d4e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f0b290d10e694b4c86355bdba583261a": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f0d43f6407674c12b85a6292284b4ba4": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_6412ab45ef6c45fd88462f76731675f9",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f09e42ab2e9f4560aa68de42fbc4d4e2",
+            "value": "Downloading metadata: 100%"
+          }
+        },
+        "f0e0d969d5f943c3ac158a6a443bceee": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_c21173370f63409b84b9f40abc202efd",
+              "IPY_MODEL_cd63bf0c96b6466586c66240f67b35a5",
+              "IPY_MODEL_ab6b00b5c38d40e4878e5de67bba6b95"
+            ],
+            "layout": "IPY_MODEL_0f2dc68b57614e79b95ddeb715f124af"
+          }
+        },
+        "f16c7f25616a478ab6ba69ce88a69724": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_bcb3bc46a920467d8441c8fe2c0081f7",
+            "max": 1296245,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_212fc0393d3a4ea9a76571c9b636ae20",
+            "value": 1296245
+          }
+        },
+        "f1a2bee7a7dc408087833912c951119d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f20da578968f43c3ac44efa032dbd6e2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f21af123c24f43498942dd4f3e91c54f": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c6656f51d29747c7a831f8b4739b8cd7",
+            "placeholder": "​",
+            "style": "IPY_MODEL_ed98bdb5c8364a6782a1883411acd5f5",
+            "value": " 518/518 [00:00&lt;00:00, 36.1kB/s]"
+          }
+        },
+        "f24b9f61a1fe4c3f86e5086676a5e5d5": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f2d79a145b3c45389a473ae2fb94e0fc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_e347c9815ff64f93884e65d882c8dc64",
+              "IPY_MODEL_df11ed2a5b2f4264b82cfd95724e7a32",
+              "IPY_MODEL_35560ff2bef140aea29689440aa8f741"
+            ],
+            "layout": "IPY_MODEL_36c149d0545d43d7ac1cb34f4e3c33bd"
+          }
+        },
+        "f2e58d8539584eebae048ed68d50a641": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_3563de5d5e394c578b7667bdae8644e6",
+            "max": 809404185,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_2040593b2df341c68670f38512b423d0",
+            "value": 809404185
+          }
+        },
+        "f387bdb0ba094db2892ed92e786886f6": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f397c359a4844fe0b43cbd55f7e45e2c": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_c8d62278ed494aa1948d4ddac0b5e94c",
+            "placeholder": "​",
+            "style": "IPY_MODEL_9ef9d3b7c4e141c99299d21e270347af",
+            "value": " 0/0 [00:00&lt;?, ?it/s]"
+          }
+        },
+        "f3cb306bf10b448ab173861f392ad1d7": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f414756091e34756a98d812bcf299f69": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f51518a3bf3b4a7582dbe26fca21ca6e": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_54e45826ac5f44d3b315e59391fbc347",
+            "placeholder": "​",
+            "style": "IPY_MODEL_f0b290d10e694b4c86355bdba583261a",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "f5449d2c5013488ab7396dc95604be0b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_1105d8a1da0146e0963254b901f6fd80",
+              "IPY_MODEL_c61132d2ccbb404ea969d7701fbc3ed7",
+              "IPY_MODEL_45684f2d86954453b3f7059f847028c4"
+            ],
+            "layout": "IPY_MODEL_053e5fb5ff954b1bb8099c07ad77c35d"
+          }
+        },
+        "f578278adfb146e8bdf89810a39d43cb": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_8f12f7c6ea604de7ab155971ffea8275",
+            "placeholder": "​",
+            "style": "IPY_MODEL_165a9c0135cb45869feb49beacb8101a",
+            "value": " 355/355 [00:00&lt;00:00, 20.0kB/s]"
+          }
+        },
+        "f59a9d0b14c348d6b9c221744c256afc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f60b9e69e69e40189644c2cde41fae18": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "f6679d2887ae4c759e6fe58b01a9d546": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "f6c554c9119f4152bd747905b3b2ade3": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f71dd43430aa4d4cb5168644a972df59": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_92f74f940eb74ceb89139e25dc1fe869",
+              "IPY_MODEL_b6168e1cb7354844a2ac17dee7a31168",
+              "IPY_MODEL_324b10e8d5ea4f1598111ce9321f5809"
+            ],
+            "layout": "IPY_MODEL_b3d5b8a11f8948d0bb7273e036841869"
+          }
+        },
+        "f75aeb7b8cc74ef488ac24f02b208535": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_d5667dae1b4d479db3745879a34b9ab5",
+            "max": 100,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_0fb032afb0904c358aaa984c8556d0c8",
+            "value": 100
+          }
+        },
+        "f794d85eed554a6ea4dabf8420da0160": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f88cf9ec7d8b4faa80017e24f99d5dc8": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "FloatProgressModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "FloatProgressModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "ProgressView",
+            "bar_style": "success",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_7b93f73af3274920ab2b51418e95cff6",
+            "max": 1516,
+            "min": 0,
+            "orientation": "horizontal",
+            "style": "IPY_MODEL_e4dd0f4da33c453e886144de5c93aeb3",
+            "value": 1516
+          }
+        },
+        "f8c2d38923c948cf8f2cf8c49ffb2c8d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f98e3325c6b64df7b028a71eb6c1aa5e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": "2",
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "f9bf6bbc52ea46bc8204f3756f2f981b": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fa5080966e724cf2901654c57dbe8abd": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HTMLModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HTMLModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HTMLView",
+            "description": "",
+            "description_tooltip": null,
+            "layout": "IPY_MODEL_cf862b504d86425f886ed6d19b55b05a",
+            "placeholder": "​",
+            "style": "IPY_MODEL_12636a29bb09482693911ac3c6ab429a",
+            "value": "Downloading data: 100%"
+          }
+        },
+        "fad67a0d8f834d6eb9609fc0ecec94c8": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fbed03f8b8ad47638a418b9f423e4c26": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fc4c72e25d9a4b648c14d03560bba0a2": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_58a4b18d859e4c47bc97f2e6ce8c6c73",
+              "IPY_MODEL_6a63b2bbe3f34bc6b9a4258a04ca9104",
+              "IPY_MODEL_9812cfa5ccd14b7aa756a383c793c2c5"
+            ],
+            "layout": "IPY_MODEL_4a2f2fa2885347aebb436467a49b8857"
+          }
+        },
+        "fc88c486f35747cd8a3e0eeaf67ebfb6": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        },
+        "fcb2db503d9a49c3b45282bebec92322": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_1384b04401ee4d5e9a7ab9574e660ee6",
+              "IPY_MODEL_86b758931e9b4f6c81b2b5d61bb0ed86",
+              "IPY_MODEL_ca8a046ed39e45f79234a10f85ed09d4"
+            ],
+            "layout": "IPY_MODEL_9d0bb9e6cae5452a8f7909340d0ab21c"
+          }
+        },
+        "fd3d2e91c7a64c2782727d2c29020fbc": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fd4d064de57d469c977318add3069303": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fdf8fb828c1d4ad6b864b9197a0aa486": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fe0bc6d3aa0b4d88a63aa611af3bf65d": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fe170e9c276f49b6927ffcbf3809de3e": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fe52a9c056f843068d5588e488f490db": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fe5fe724aaa14f2bb80e84fc589103fc": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fe66b6883afa471eb687430534bd0820": {
+          "model_module": "@jupyter-widgets/base",
+          "model_module_version": "1.2.0",
+          "model_name": "LayoutModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/base",
+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "LayoutView",
+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
+            "display": null,
+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
+            "object_position": null,
+            "order": null,
+            "overflow": null,
+            "overflow_x": null,
+            "overflow_y": null,
+            "padding": null,
+            "right": null,
+            "top": null,
+            "visibility": null,
+            "width": null
+          }
+        },
+        "fe92ba127a624524bfe051a6040b4c45": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "DescriptionStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "DescriptionStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "description_width": ""
+          }
+        },
+        "fee13e5677e84373a18a0f68feb13ab5": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "HBoxModel",
+          "state": {
+            "_dom_classes": [],
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "HBoxModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/controls",
+            "_view_module_version": "1.5.0",
+            "_view_name": "HBoxView",
+            "box_style": "",
+            "children": [
+              "IPY_MODEL_7982ba1cd95e4347ad3fca29f38d0638",
+              "IPY_MODEL_f75aeb7b8cc74ef488ac24f02b208535",
+              "IPY_MODEL_008e77e9b3cb4cc4b37e875cab3f3d6c"
+            ],
+            "layout": "IPY_MODEL_e0da7e4a45a846c0ac14269e5bbb77f8"
+          }
+        },
+        "ff830930e9e04bdaa73f57e4eafe1979": {
+          "model_module": "@jupyter-widgets/controls",
+          "model_module_version": "1.5.0",
+          "model_name": "ProgressStyleModel",
+          "state": {
+            "_model_module": "@jupyter-widgets/controls",
+            "_model_module_version": "1.5.0",
+            "_model_name": "ProgressStyleModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
+            "_view_name": "StyleView",
+            "bar_color": null,
+            "description_width": ""
+          }
+        }
+      }
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/src/transformers/models/idefics2/fine_tune_idefics2.ipynb b/src/transformers/models/idefics2/fine_tune_idefics2.ipynb
new file mode 100644
index 00000000000000..244f34181979ac
--- /dev/null
+++ b/src/transformers/models/idefics2/fine_tune_idefics2.ipynb
@@ -0,0 +1,851 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.environ[\"CUDA_DEVICE_ORDER\"] = \"PCI_BUS_ID\"\n",
+    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/niels/python_projects/transformers/env/lib/python3.8/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n",
+      "`low_cpu_mem_usage` was None, now set to True since model is quantized.\n",
+      "Loading checkpoint shards: 100%|██████████| 7/7 [00:06<00:00,  1.12it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "from peft import LoraConfig\n",
+    "from transformers import BitsAndBytesConfig, Idefics2ForConditionalGeneration\n",
+    "\n",
+    "DEVICE = \"cuda:0\"\n",
+    "USE_LORA = False\n",
+    "USE_QLORA = True\n",
+    "\n",
+    "# Three options for training, from the lowest precision training to the highest precision training:\n",
+    "# - QLora\n",
+    "# - Standard Lora\n",
+    "# - Full fine-tuning\n",
+    "if USE_QLORA or USE_LORA:\n",
+    "    lora_config = LoraConfig(\n",
+    "        r=8,\n",
+    "        lora_alpha=8,\n",
+    "        lora_dropout=0.1,\n",
+    "        target_modules='.*(text_model|modality_projection|perceiver_resampler).*(down_proj|gate_proj|up_proj|k_proj|q_proj|v_proj|o_proj).*$',\n",
+    "        use_dora=False if USE_QLORA else True,\n",
+    "        init_lora_weights=\"gaussian\"\n",
+    "    )\n",
+    "    if USE_QLORA:\n",
+    "        bnb_config = BitsAndBytesConfig(\n",
+    "            load_in_4bit=True,\n",
+    "            bnb_4bit_quant_type=\"nf4\",\n",
+    "            bnb_4bit_compute_dtype=torch.float16\n",
+    "        )\n",
+    "    model = Idefics2ForConditionalGeneration.from_pretrained(\n",
+    "        \"HuggingFaceM4/idefics2-8b\",\n",
+    "        torch_dtype=torch.float16,\n",
+    "        quantization_config=bnb_config if USE_QLORA else None,\n",
+    "    )\n",
+    "    model.add_adapter(lora_config)\n",
+    "    model.enable_adapters()\n",
+    "else:\n",
+    "    model = Idefics2ForConditionalGeneration.from_pretrained(\n",
+    "        \"HuggingFaceM4/idefics2-8b\",\n",
+    "        torch_dtype=torch.float16,\n",
+    "        _attn_implementation=\"flash_attention_2\", # Only available on A100 or H100\n",
+    "    ).to(DEVICE)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset\n",
+    "\n",
+    "dataset = load_dataset(\"naver-clova-ix/cord-v2\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatasetDict({\n",
+       "    train: Dataset({\n",
+       "        features: ['image', 'ground_truth'],\n",
+       "        num_rows: 800\n",
+       "    })\n",
+       "    validation: Dataset({\n",
+       "        features: ['image', 'ground_truth'],\n",
+       "        num_rows: 100\n",
+       "    })\n",
+       "    test: Dataset({\n",
+       "        features: ['image', 'ground_truth'],\n",
+       "        num_rows: 100\n",
+       "    })\n",
+       "})"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/jpeg": "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",
+      "image/png": "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",
+      "text/plain": [
+       "<PIL.Image.Image image mode=RGB size=259x388>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_example = dataset[\"train\"][0]\n",
+    "# check the image\n",
+    "resized_image = train_example[\"image\"]\n",
+    "width, height = resized_image.size\n",
+    "resized_image.resize((int(0.3*width), int(0.3*height)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'menu': [{'nm': 'Nasi Campur Bali', 'cnt': '1 x', 'price': '75,000'}, {'nm': 'Bbk Bengil Nasi', 'cnt': '1 x', 'price': '125,000'}, {'nm': 'MilkShake Starwb', 'cnt': '1 x', 'price': '37,000'}, {'nm': 'Ice Lemon Tea', 'cnt': '1 x', 'price': '24,000'}, {'nm': 'Nasi Ayam Dewata', 'cnt': '1 x', 'price': '70,000'}, {'nm': 'Free Ice Tea', 'cnt': '3 x', 'price': '0'}, {'nm': 'Organic Green Sa', 'cnt': '1 x', 'price': '65,000'}, {'nm': 'Ice Tea', 'cnt': '1 x', 'price': '18,000'}, {'nm': 'Ice Orange', 'cnt': '1 x', 'price': '29,000'}, {'nm': 'Ayam Suir Bali', 'cnt': '1 x', 'price': '85,000'}, {'nm': 'Tahu Goreng', 'cnt': '2 x', 'price': '36,000'}, {'nm': 'Tempe Goreng', 'cnt': '2 x', 'price': '36,000'}, {'nm': 'Tahu Telor Asin', 'cnt': '1 x', 'price': '40,000.'}, {'nm': 'Nasi Goreng Samb', 'cnt': '1 x', 'price': '70,000'}, {'nm': 'Bbk Panggang Sam', 'cnt': '3 x', 'price': '366,000'}, {'nm': 'Ayam Sambal Hija', 'cnt': '1 x', 'price': '92,000'}, {'nm': 'Hot Tea', 'cnt': '2 x', 'price': '44,000'}, {'nm': 'Ice Kopi', 'cnt': '1 x', 'price': '32,000'}, {'nm': 'Tahu Telor Asin', 'cnt': '1 x', 'price': '40,000'}, {'nm': 'Free Ice Tea', 'cnt': '1 x', 'price': '0'}, {'nm': 'Bebek Street', 'cnt': '1 x', 'price': '44,000'}, {'nm': 'Ice Tea Tawar', 'cnt': '1 x', 'price': '18,000'}], 'sub_total': {'subtotal_price': '1,346,000', 'service_price': '100,950', 'tax_price': '144,695', 'etc': '-45'}, 'total': {'total_price': '1,591,600'}}\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "\n",
+    "ground_truth = json.loads(train_example[\"ground_truth\"])\n",
+    "print(ground_truth[\"gt_parse\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create PyTorch dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-04-29 14:53:34.445416: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "2024-04-29 14:53:35.100124: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
+      "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import random\n",
+    "from typing import Any, List\n",
+    "\n",
+    "from torch.utils.data import Dataset\n",
+    "from transformers import AutoProcessor\n",
+    "\n",
+    "added_tokens = []\n",
+    "processor = AutoProcessor.from_pretrained(\"HuggingFaceM4/idefics2-8b\", do_image_splitting=False)\n",
+    "\n",
+    "\n",
+    "class CustomDataset(Dataset):\n",
+    "  def __init__(self, hf_dataset, split, sort_json_key: bool = True,):\n",
+    "    self.dataset = hf_dataset[split]\n",
+    "    self.split = split\n",
+    "    self.sort_json_key = sort_json_key\n",
+    "\n",
+    "    ground_truth_token_sequences = []\n",
+    "    for sample in self.dataset:\n",
+    "        ground_truth = json.loads(sample[\"ground_truth\"])\n",
+    "        if \"gt_parses\" in ground_truth:  # some datasets have multiple ground truths available, e.g. DocVQA\n",
+    "            assert isinstance(ground_truth[\"gt_parses\"], list)\n",
+    "            ground_truth_jsons = ground_truth[\"gt_parses\"]\n",
+    "        else:\n",
+    "            assert \"gt_parse\" in ground_truth and isinstance(ground_truth[\"gt_parse\"], dict)\n",
+    "            ground_truth_jsons = [ground_truth[\"gt_parse\"]]\n",
+    "\n",
+    "        ground_truth_token_sequences.append(\n",
+    "            [\n",
+    "                self.json2token(\n",
+    "                    ground_truth_json,\n",
+    "                    update_special_tokens_for_json_key=self.split == \"train\",\n",
+    "                    sort_json_key=self.sort_json_key,\n",
+    "                )\n",
+    "                for ground_truth_json in ground_truth_jsons  # load json from list of json\n",
+    "            ]\n",
+    "        )\n",
+    "\n",
+    "    self.ground_truth_token_sequences = ground_truth_token_sequences\n",
+    "\n",
+    "  def json2token(self, obj: Any, update_special_tokens_for_json_key: bool = True, sort_json_key: bool = True):\n",
+    "        \"\"\"\n",
+    "        Convert an ordered JSON object into a token sequence\n",
+    "        \"\"\"\n",
+    "        if type(obj) == dict:\n",
+    "            if len(obj) == 1 and \"text_sequence\" in obj:\n",
+    "                return obj[\"text_sequence\"]\n",
+    "            else:\n",
+    "                output = \"\"\n",
+    "                if sort_json_key:\n",
+    "                    keys = sorted(obj.keys(), reverse=True)\n",
+    "                else:\n",
+    "                    keys = obj.keys()\n",
+    "                for k in keys:\n",
+    "                    if update_special_tokens_for_json_key:\n",
+    "                        self.add_tokens([fr\"<s_{k}>\", fr\"</s_{k}>\"])\n",
+    "                    output += (\n",
+    "                        fr\"<s_{k}>\"\n",
+    "                        + self.json2token(obj[k], update_special_tokens_for_json_key, sort_json_key)\n",
+    "                        + fr\"</s_{k}>\"\n",
+    "                    )\n",
+    "                return output\n",
+    "        elif type(obj) == list:\n",
+    "            return r\"<sep/>\".join(\n",
+    "                [self.json2token(item, update_special_tokens_for_json_key, sort_json_key) for item in obj]\n",
+    "            )\n",
+    "        else:\n",
+    "            obj = str(obj)\n",
+    "            if f\"<{obj}/>\" in added_tokens:\n",
+    "                obj = f\"<{obj}/>\"  # for categorical special tokens\n",
+    "            return obj\n",
+    "    \n",
+    "  def add_tokens(self, list_of_tokens: List[str]):\n",
+    "      \"\"\"\n",
+    "      Add special tokens to tokenizer and resize the token embeddings of the decoder\n",
+    "      \"\"\"\n",
+    "      newly_added_num = processor.tokenizer.add_tokens(list_of_tokens)\n",
+    "      if newly_added_num > 0:\n",
+    "          model.resize_token_embeddings(len(processor.tokenizer))\n",
+    "          added_tokens.extend(list_of_tokens)\n",
+    "  \n",
+    "  def __len__(self):\n",
+    "    return len(self.dataset)\n",
+    "  \n",
+    "  def __getitem__(self, idx):\n",
+    "    example = self.dataset[idx]\n",
+    "    image = example[\"image\"]\n",
+    "    target_sequence = random.choice(self.ground_truth_token_sequences[idx])  # can be more than one, e.g., DocVQA\n",
+    "\n",
+    "    return image, target_sequence"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'train': SplitInfo(name='train', num_bytes=1840803702, num_examples=800, shard_lengths=[400, 400], dataset_name='cord-v2'),\n",
+       " 'validation': SplitInfo(name='validation', num_bytes=242513269, num_examples=100, shard_lengths=None, dataset_name='cord-v2'),\n",
+       " 'test': SplitInfo(name='test', num_bytes=235013906, num_examples=100, shard_lengths=None, dataset_name='cord-v2')}"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset[\"train\"].info.splits"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_dataset = CustomDataset(hf_dataset=dataset, split=\"train\")\n",
+    "eval_dataset = CustomDataset(hf_dataset=dataset, split=\"validation\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<PIL.PngImagePlugin.PngImageFile image mode=RGB size=864x1296>,\n",
+       " '<s_total><s_total_price>1,591,600</s_total_price></s_total><s_sub_total><s_tax_price>144,695</s_tax_price><s_subtotal_price>1,346,000</s_subtotal_price><s_service_price>100,950</s_service_price><s_etc>-45</s_etc></s_sub_total><s_menu><s_price>75,000</s_price><s_nm>Nasi Campur Bali</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>125,000</s_price><s_nm>Bbk Bengil Nasi</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>37,000</s_price><s_nm>MilkShake Starwb</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>24,000</s_price><s_nm>Ice Lemon Tea</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>70,000</s_price><s_nm>Nasi Ayam Dewata</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>0</s_price><s_nm>Free Ice Tea</s_nm><s_cnt>3 x</s_cnt><sep/><s_price>65,000</s_price><s_nm>Organic Green Sa</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>18,000</s_price><s_nm>Ice Tea</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>29,000</s_price><s_nm>Ice Orange</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>85,000</s_price><s_nm>Ayam Suir Bali</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>36,000</s_price><s_nm>Tahu Goreng</s_nm><s_cnt>2 x</s_cnt><sep/><s_price>36,000</s_price><s_nm>Tempe Goreng</s_nm><s_cnt>2 x</s_cnt><sep/><s_price>40,000.</s_price><s_nm>Tahu Telor Asin</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>70,000</s_price><s_nm>Nasi Goreng Samb</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>366,000</s_price><s_nm>Bbk Panggang Sam</s_nm><s_cnt>3 x</s_cnt><sep/><s_price>92,000</s_price><s_nm>Ayam Sambal Hija</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>44,000</s_price><s_nm>Hot Tea</s_nm><s_cnt>2 x</s_cnt><sep/><s_price>32,000</s_price><s_nm>Ice Kopi</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>40,000</s_price><s_nm>Tahu Telor Asin</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>0</s_price><s_nm>Free Ice Tea</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>44,000</s_price><s_nm>Bebek Street</s_nm><s_cnt>1 x</s_cnt><sep/><s_price>18,000</s_price><s_nm>Ice Tea Tawar</s_nm><s_cnt>1 x</s_cnt></s_menu>')"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_dataset[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "54"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(added_tokens)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['<s_total>', '</s_total>', '<s_total_price>', '</s_total_price>', '<s_sub_total>', '</s_sub_total>', '<s_tax_price>', '</s_tax_price>', '<s_subtotal_price>', '</s_subtotal_price>', '<s_service_price>', '</s_service_price>', '<s_etc>', '</s_etc>', '<s_menu>', '</s_menu>', '<s_price>', '</s_price>', '<s_nm>', '</s_nm>', '<s_cnt>', '</s_cnt>', '<s_sub>', '</s_sub>', '<s_menutype_cnt>', '</s_menutype_cnt>', '<s_menuqty_cnt>', '</s_menuqty_cnt>', '<s_changeprice>', '</s_changeprice>', '<s_cashprice>', '</s_cashprice>', '<s_discount_price>', '</s_discount_price>', '<s_unitprice>', '</s_unitprice>', '<s_total_etc>', '</s_total_etc>', '<s_creditcardprice>', '</s_creditcardprice>', '<s_num>', '</s_num>', '<s_discountprice>', '</s_discountprice>', '<s_emoneyprice>', '</s_emoneyprice>', '<s_void_menu>', '</s_void_menu>', '<s_othersvc_price>', '</s_othersvc_price>', '<s_vatyn>', '</s_vatyn>', '<s_itemsubtotal>', '</s_itemsubtotal>']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(added_tokens)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Define DataCollator"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MyDataCollator:\n",
+    "    def __init__(self, processor):\n",
+    "        self.processor = processor\n",
+    "        self.image_token_id = processor.tokenizer.additional_special_tokens_ids[\n",
+    "            processor.tokenizer.additional_special_tokens.index(\"<image>\")\n",
+    "        ]\n",
+    "\n",
+    "    def __call__(self, examples):\n",
+    "        texts = []\n",
+    "        images = []\n",
+    "        for example in examples:\n",
+    "            image, ground_truth = example\n",
+    "            messages = [\n",
+    "                {\n",
+    "                    \"role\": \"user\",\n",
+    "                    \"content\": [\n",
+    "                        {\"type\": \"text\", \"text\": \"Extract JSON.\"},\n",
+    "                        {\"type\": \"image\"},\n",
+    "                    ]\n",
+    "                },\n",
+    "                {\n",
+    "                    \"role\": \"assistant\",\n",
+    "                    \"content\": [\n",
+    "                        {\"type\": \"text\", \"text\": ground_truth}\n",
+    "                    ]\n",
+    "                }\n",
+    "            ]\n",
+    "            text = processor.apply_chat_template(messages, add_generation_prompt=False)\n",
+    "            texts.append(text.strip())\n",
+    "            images.append([image])\n",
+    "\n",
+    "        batch = processor(text=texts, images=images, return_tensors=\"pt\", padding=True)\n",
+    "\n",
+    "        labels = batch[\"input_ids\"].clone()\n",
+    "        labels[labels == processor.tokenizer.pad_token_id] = self.image_token_id\n",
+    "        batch[\"labels\"] = labels\n",
+    "\n",
+    "        return batch\n",
+    "\n",
+    "data_collator = MyDataCollator(processor)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Verify data (by creating dataloader)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "input_ids torch.Size([2, 387])\n",
+      "attention_mask torch.Size([2, 387])\n",
+      "pixel_values torch.Size([2, 1, 3, 980, 653])\n",
+      "pixel_attention_mask torch.Size([2, 1, 980, 653])\n",
+      "labels torch.Size([2, 387])\n"
+     ]
+    }
+   ],
+   "source": [
+    "from torch.utils.data import DataLoader\n",
+    "\n",
+    "train_dataloader = DataLoader(train_dataset, collate_fn=data_collator, batch_size=2, shuffle=True)\n",
+    "batch = next(iter(train_dataloader))\n",
+    "for k,v in batch.items():\n",
+    "  print(k,v.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['<unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><s> User: Extract JSON.<fake_token_around_image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><fake_token_around_image><end_of_utterance> \\nAssistant:<s_total><s_total_price>15.000</s_total_price></s_total><s_sub_total><s_subtotal_price>15.000</s_subtotal_price></s_sub_total><s_menu><s_unitprice>@15.000</s_unitprice><s_price>15.000</s_price><s_nm>Es Kopi Susu</s_nm><s_cnt>1x</s_cnt></s_menu><end_of_utterance>',\n",
+       " '<s> User: Extract JSON.<fake_token_around_image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><fake_token_around_image><end_of_utterance> \\nAssistant:<s_total><s_total_price>70,000</s_total_price><s_creditcardprice>70,000</s_creditcardprice><s_changeprice>0</s_changeprice></s_total><s_sub_total><s_subtotal_price>70,000</s_subtotal_price></s_sub_total><s_menu><s_unitprice>70,000</s_unitprice><s_sub><s_nm>Si1ky Lychee</s_nm><s_cnt>2x</s_cnt><sep/><s_nm>Si1ky Mango</s_nm><s_cnt>1x</s_cnt><sep/><s_nm>Si1ky Cotton Candy</s_nm><s_cnt>1x</s_cnt><sep/><s_nm>Si1ky Green Tea</s_nm><s_cnt>1x</s_cnt><sep/><s_nm>Si1ky Chocolate</s_nm><s_cnt>1x</s_cnt></s_sub><s_price>70,000</s_price><s_nm>Puyo 6 (Package)</s_nm><s_cnt>1x</s_cnt></s_menu><end_of_utterance>']"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "processor.batch_decode(batch[\"input_ids\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import Levenshtein\n",
+    "import numpy as np\n",
+    "\n",
+    "\n",
+    "def normalized_levenshtein(s1, s2):\n",
+    "    len_s1, len_s2 = len(s1), len(s2)\n",
+    "    distance = Levenshtein.distance(s1, s2)\n",
+    "    return distance / max(len_s1, len_s2)\n",
+    "\n",
+    "def similarity_score(a_ij, o_q_i, tau=0.5):\n",
+    "    nl = normalized_levenshtein(a_ij, o_q_i)\n",
+    "    return 1 - nl if nl < tau else 0\n",
+    "\n",
+    "def postprocess_text(preds, labels):\n",
+    "        preds = [pred.strip() for pred in preds]\n",
+    "        labels = [[label.strip()] for label in labels]\n",
+    "\n",
+    "        return preds, labels\n",
+    "\n",
+    "def compute_metrics(eval_preds):\n",
+    "    # Get the predicted and ground truth token sequences\n",
+    "    preds, labels = eval_preds\n",
+    "\n",
+    "    print(\"Type of preds:\", type(preds))\n",
+    "    print(\"Type of first prediction:\", type(preds))\n",
+    "    print(\"Type of prediction:\", type(preds[0]))\n",
+    "\n",
+    "    print(\"Type of labels:\", type(labels))\n",
+    "    print(\"Type of first labels:\", type(labels))\n",
+    "    print(\"Type of labels:\", type(labels[0]))\n",
+    "\n",
+    "    if isinstance(preds, tuple):\n",
+    "        preds = preds[0]\n",
+    "    # Replace -100s used for padding as we can't decode them\n",
+    "    preds = np.where(preds != -100, preds, processor.tokenizer.pad_token_id)\n",
+    "    decoded_preds = processor.batch_decode(preds, skip_special_tokens=True)\n",
+    "    labels = np.where(labels != -100, labels, processor.tokenizer.pad_token_id)\n",
+    "    decoded_labels = processor.batch_decode(labels, skip_special_tokens=True)\n",
+    "\n",
+    "    # Some simple post-processing\n",
+    "    decoded_preds, decoded_labels = postprocess_text(decoded_preds, decoded_labels)\n",
+    "\n",
+    "    assert len(labels) == len(decoded_preds), \"Length of labels and decoded predictions must match.\"\n",
+    "\n",
+    "    N = len(labels)\n",
+    "    total_score = 0\n",
+    "\n",
+    "    for i in range(N):\n",
+    "        a_i = labels[i]\n",
+    "        o_q_i = decoded_preds[i]\n",
+    "        if o_q_i == \"\":\n",
+    "            print(\"Warning: Skipped an empty prediction.\")\n",
+    "            max_score = 0\n",
+    "        else:\n",
+    "            max_score = max(similarity_score(a_ij, o_q_i) for a_ij in a_i)\n",
+    "\n",
+    "        total_score += max_score\n",
+    "\n",
+    "    return {\"levenshtein\": total_score / N}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/niels/python_projects/transformers/src/transformers/training_args.py:1463: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead\n",
+      "  warnings.warn(\n",
+      "Detected kernel version 5.4.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.\n"
+     ]
+    }
+   ],
+   "source": [
+    "from transformers import TrainingArguments, Trainer\n",
+    "\n",
+    "training_args = TrainingArguments(\n",
+    "    num_train_epochs=2,\n",
+    "    per_device_train_batch_size=2,\n",
+    "    per_device_eval_batch_size=8,\n",
+    "    gradient_accumulation_steps=8,\n",
+    "    warmup_steps=50,\n",
+    "    learning_rate=1e-4,\n",
+    "    weight_decay=0.01,\n",
+    "    logging_steps=25,\n",
+    "    output_dir=\"idefics2_ft_tutorial\",\n",
+    "    evaluation_strategy=\"steps\",\n",
+    "    eval_steps=1,\n",
+    "    save_strategy=\"steps\",\n",
+    "    save_steps=250,\n",
+    "    save_total_limit=1,\n",
+    "    # evaluation_strategy=\"epoch\",\n",
+    "    fp16=True,\n",
+    "    # push_to_hub_model_id=\"idefics2-8b-docvqa-finetuned-tutorial\",\n",
+    "    remove_unused_columns=False,\n",
+    "    report_to=\"none\",\n",
+    "    eval_do_concat_batches=False,\n",
+    ")\n",
+    "\n",
+    "# important: we need to disable caching during training\n",
+    "model.config.use_cache = False\n",
+    "\n",
+    "trainer = Trainer(\n",
+    "    model=model,\n",
+    "    args=training_args,\n",
+    "    data_collator=data_collator,\n",
+    "    train_dataset=train_dataset,\n",
+    "    eval_dataset=eval_dataset, # You can also evaluate (loss) on the eval set, note that it will incur some additional GPU memory,\n",
+    "    compute_metrics=compute_metrics,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+      "To disable this warning, you can either:\n",
+      "\t- Avoid using `tokenizers` before the fork if possible\n",
+      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+     ]
+    }
+   ],
+   "source": [
+    "!echo $CUDA_VISIBLE_DEVICES"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.config.use_cache"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "trainer.train()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Inference\n",
+    "\n",
+    "Let's see if the model has learned something."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_example = dataset[\"test\"][0]\n",
+    "test_image = test_example[\"image\"]\n",
+    "test_image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# prepare image and prompt for the model\n",
+    "messages = [\n",
+    "    {\n",
+    "        \"role\": \"user\",\n",
+    "        \"content\": [\n",
+    "            {\"type\": \"text\", \"text\": \"Extract JSON.\"},\n",
+    "            {\"type\": \"image\"},\n",
+    "        ]\n",
+    "    },\n",
+    "]\n",
+    "prompt = processor.apply_chat_template(messages, add_generation_prompt=True)\n",
+    "print(prompt)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "inputs = processor(text=prompt, images=[test_image], return_tensors=\"pt\")\n",
+    "inputs = {k: v.to(DEVICE) for k, v in inputs.items()}\n",
+    "\n",
+    "# Generate\n",
+    "generated_ids = model.generate(**inputs, max_new_tokens=500)\n",
+    "generated_texts = processor.batch_decode(generated_ids, skip_special_tokens=True)\n",
+    "\n",
+    "print(generated_texts)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import re\n",
+    "\n",
+    "# let's turn that into JSON\n",
+    "def token2json(tokens, is_inner_value=False, added_vocab=None):\n",
+    "        \"\"\"\n",
+    "        Convert a (generated) token sequence into an ordered JSON format.\n",
+    "        \"\"\"\n",
+    "        if added_vocab is None:\n",
+    "            added_vocab = processor.tokenizer.get_added_vocab()\n",
+    "\n",
+    "        output = {}\n",
+    "\n",
+    "        while tokens:\n",
+    "            start_token = re.search(r\"<s_(.*?)>\", tokens, re.IGNORECASE)\n",
+    "            if start_token is None:\n",
+    "                break\n",
+    "            key = start_token.group(1)\n",
+    "            key_escaped = re.escape(key)\n",
+    "\n",
+    "            end_token = re.search(rf\"</s_{key_escaped}>\", tokens, re.IGNORECASE)\n",
+    "            start_token = start_token.group()\n",
+    "            if end_token is None:\n",
+    "                tokens = tokens.replace(start_token, \"\")\n",
+    "            else:\n",
+    "                end_token = end_token.group()\n",
+    "                start_token_escaped = re.escape(start_token)\n",
+    "                end_token_escaped = re.escape(end_token)\n",
+    "                content = re.search(\n",
+    "                    f\"{start_token_escaped}(.*?){end_token_escaped}\", tokens, re.IGNORECASE | re.DOTALL\n",
+    "                )\n",
+    "                if content is not None:\n",
+    "                    content = content.group(1).strip()\n",
+    "                    if r\"<s_\" in content and r\"</s_\" in content:  # non-leaf node\n",
+    "                        value = token2json(content, is_inner_value=True, added_vocab=added_vocab)\n",
+    "                        if value:\n",
+    "                            if len(value) == 1:\n",
+    "                                value = value[0]\n",
+    "                            output[key] = value\n",
+    "                    else:  # leaf nodes\n",
+    "                        output[key] = []\n",
+    "                        for leaf in content.split(r\"<sep/>\"):\n",
+    "                            leaf = leaf.strip()\n",
+    "                            if leaf in added_vocab and leaf[0] == \"<\" and leaf[-2:] == \"/>\":\n",
+    "                                leaf = leaf[1:-2]  # for categorical special tokens\n",
+    "                            output[key].append(leaf)\n",
+    "                        if len(output[key]) == 1:\n",
+    "                            output[key] = output[key][0]\n",
+    "\n",
+    "                tokens = tokens[tokens.find(end_token) + len(end_token) :].strip()\n",
+    "                if tokens[:6] == r\"<sep/>\":  # non-leaf nodes\n",
+    "                    return [output] + token2json(tokens[6:], is_inner_value=True, added_vocab=added_vocab)\n",
+    "\n",
+    "        if len(output):\n",
+    "            return [output] if is_inner_value else output\n",
+    "        else:\n",
+    "            return [] if is_inner_value else {\"text_sequence\": tokens}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "generated_json = token2json(generated_texts[0])\n",
+    "print(generated_json)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for key, value in generated_json.items():\n",
+    "    print(key, value)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/src/transformers/models/idefics2/fine_tune_idefics2.py b/src/transformers/models/idefics2/fine_tune_idefics2.py
new file mode 100644
index 00000000000000..dedfda82e72563
--- /dev/null
+++ b/src/transformers/models/idefics2/fine_tune_idefics2.py
@@ -0,0 +1,512 @@
+"""
+Fine-tune Idefics2 by tweaking the `Seq2SeqTrainer` class.
+
+One can run the script using `CUDA_VISIBLE_DEVICES=3 python src/transformers/models/idefics2/fine_tune_idefics2.py`.
+"""
+
+import json
+import random
+from typing import Any, Dict, List, Optional, Tuple, Union
+
+import Levenshtein
+import numpy as np
+import requests
+import torch
+from datasets import load_dataset
+from peft import LoraConfig
+from PIL import Image
+from torch import nn
+from torch.utils.data import Dataset
+
+from transformers import (
+    AutoProcessor,
+    BitsAndBytesConfig,
+    GenerationConfig,
+    Idefics2ForConditionalGeneration,
+    Seq2SeqTrainer,
+    Seq2SeqTrainingArguments,
+)
+
+
+DEVICE = "cuda:0"
+USE_LORA = False
+USE_QLORA = True
+
+## Load model
+
+# Three options for training, from the lowest precision training to the highest precision training:
+# - QLora
+# - Standard Lora
+# - Full fine-tuning
+if USE_QLORA or USE_LORA:
+    lora_config = LoraConfig(
+        r=8,
+        lora_alpha=8,
+        lora_dropout=0.1,
+        target_modules=".*(text_model|modality_projection|perceiver_resampler).*(down_proj|gate_proj|up_proj|k_proj|q_proj|v_proj|o_proj).*$",
+        use_dora=False if USE_QLORA else True,
+        init_lora_weights="gaussian",
+    )
+    if USE_QLORA:
+        bnb_config = BitsAndBytesConfig(
+            load_in_4bit=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=torch.float16
+        )
+    model = Idefics2ForConditionalGeneration.from_pretrained(
+        "HuggingFaceM4/idefics2-8b",
+        torch_dtype=torch.float16,
+        quantization_config=bnb_config if USE_QLORA else None,
+    )
+    model.add_adapter(lora_config)
+    model.enable_adapters()
+else:
+    model = Idefics2ForConditionalGeneration.from_pretrained(
+        "HuggingFaceM4/idefics2-8b",
+        torch_dtype=torch.float16,
+        _attn_implementation="flash_attention_2",  # Only available on A100 or H100
+    ).to(DEVICE)
+
+
+## Load dataset
+dataset = load_dataset("naver-clova-ix/cord-v2")
+
+## Create PyTorch dataset
+added_tokens = []
+processor = AutoProcessor.from_pretrained("HuggingFaceM4/idefics2-8b", do_image_splitting=False)
+
+
+class CustomDataset(Dataset):
+    def __init__(
+        self,
+        hf_dataset,
+        split,
+        sort_json_key: bool = True,
+    ):
+        self.dataset = hf_dataset[split]
+        self.split = split
+        self.sort_json_key = sort_json_key
+
+        ground_truth_token_sequences = []
+        for sample in self.dataset:
+            ground_truth = json.loads(sample["ground_truth"])
+            if "gt_parses" in ground_truth:  # some datasets have multiple ground truths available, e.g. DocVQA
+                assert isinstance(ground_truth["gt_parses"], list)
+                ground_truth_jsons = ground_truth["gt_parses"]
+            else:
+                assert "gt_parse" in ground_truth and isinstance(ground_truth["gt_parse"], dict)
+                ground_truth_jsons = [ground_truth["gt_parse"]]
+
+            ground_truth_token_sequences.append(
+                [
+                    self.json2token(
+                        ground_truth_json,
+                        update_special_tokens_for_json_key=self.split == "train",
+                        sort_json_key=self.sort_json_key,
+                    )
+                    for ground_truth_json in ground_truth_jsons  # load json from list of json
+                ]
+            )
+
+        self.ground_truth_token_sequences = ground_truth_token_sequences
+
+    def json2token(self, obj: Any, update_special_tokens_for_json_key: bool = True, sort_json_key: bool = True):
+        """
+        Convert an ordered JSON object into a token sequence
+        """
+        if type(obj) == dict:
+            if len(obj) == 1 and "text_sequence" in obj:
+                return obj["text_sequence"]
+            else:
+                output = ""
+                if sort_json_key:
+                    keys = sorted(obj.keys(), reverse=True)
+                else:
+                    keys = obj.keys()
+                for k in keys:
+                    if update_special_tokens_for_json_key:
+                        self.add_tokens([rf"<s_{k}>", rf"</s_{k}>"])
+                    output += (
+                        rf"<s_{k}>"
+                        + self.json2token(obj[k], update_special_tokens_for_json_key, sort_json_key)
+                        + rf"</s_{k}>"
+                    )
+                return output
+        elif type(obj) == list:
+            return r"<sep/>".join(
+                [self.json2token(item, update_special_tokens_for_json_key, sort_json_key) for item in obj]
+            )
+        else:
+            obj = str(obj)
+            if f"<{obj}/>" in added_tokens:
+                obj = f"<{obj}/>"  # for categorical special tokens
+            return obj
+
+    def add_tokens(self, list_of_tokens: List[str]):
+        """
+        Add special tokens to tokenizer and resize the token embeddings of the decoder
+        """
+        newly_added_num = processor.tokenizer.add_tokens(list_of_tokens)
+        if newly_added_num > 0:
+            model.resize_token_embeddings(len(processor.tokenizer))
+            added_tokens.extend(list_of_tokens)
+
+    def __len__(self):
+        return len(self.dataset)
+
+    def __getitem__(self, idx):
+        example = self.dataset[idx]
+        image = example["image"]
+        target_sequence = random.choice(self.ground_truth_token_sequences[idx])  # can be more than one, e.g., DocVQA
+
+        return image, target_sequence
+
+
+train_dataset = CustomDataset(hf_dataset=dataset, split="train")
+eval_dataset = CustomDataset(hf_dataset=dataset, split="validation")
+
+
+## Define data collator
+class MyDataCollator:
+    def __init__(self, processor):
+        self.processor = processor
+        self.image_token_id = processor.tokenizer.additional_special_tokens_ids[
+            processor.tokenizer.additional_special_tokens.index("<image>")
+        ]
+
+    def __call__(self, examples):
+        texts = []
+        images = []
+        for example in examples:
+            image, ground_truth = example
+            messages = [
+                {
+                    "role": "user",
+                    "content": [
+                        {"type": "text", "text": "Extract JSON."},
+                        {"type": "image"},
+                    ],
+                },
+                {"role": "assistant", "content": [{"type": "text", "text": ground_truth}]},
+            ]
+            text = processor.apply_chat_template(messages, add_generation_prompt=False)
+            texts.append(text.strip())
+            images.append([image])
+
+        batch = processor(
+            text=texts, images=images, return_tensors="pt", truncation=True, padding="max_length", max_length=200
+        )
+
+        labels = batch["input_ids"].clone()
+        labels[labels == processor.tokenizer.pad_token_id] = self.image_token_id
+        batch["labels"] = labels
+
+        return batch
+
+
+data_collator = MyDataCollator(processor)
+
+
+## Define metrics
+
+
+def normalized_levenshtein(s1, s2):
+    len_s1, len_s2 = len(s1), len(s2)
+    distance = Levenshtein.distance(s1, s2)
+    return distance / max(len_s1, len_s2)
+
+
+def similarity_score(a_ij, o_q_i, tau=0.5):
+    nl = normalized_levenshtein(a_ij, o_q_i)
+    return 1 - nl if nl < tau else 0
+
+
+def average_normalized_levenshtein_similarity(ground_truth, predicted_answers):
+    assert len(ground_truth) == len(predicted_answers), "Length of ground_truth and predicted_answers must match."
+
+    N = len(ground_truth)
+    total_score = 0
+
+    for i in range(N):
+        a_i = ground_truth[i]
+        o_q_i = predicted_answers[i]
+        if o_q_i == "":
+            print("Warning: Skipped an empty prediction.")
+            max_score = 0
+        else:
+            max_score = max(similarity_score(a_ij, o_q_i) for a_ij in a_i)
+
+        total_score += max_score
+
+    return total_score / N
+
+
+def postprocess_text(preds, labels):
+    preds = [pred.strip() for pred in preds]
+    labels = [[label.strip()] for label in labels]
+
+    return preds, labels
+
+
+def compute_metrics(eval_preds):
+    preds, labels = eval_preds
+    if isinstance(preds, tuple):
+        preds = preds[0]
+    # Replace -100s used for padding as we can't decode them
+    preds = np.where(preds != -100, preds, processor.tokenizer.pad_token_id)
+    decoded_preds = processor.batch_decode(preds, skip_special_tokens=True)
+    labels = np.where(labels != -100, labels, processor.tokenizer.pad_token_id)
+    decoded_labels = processor.batch_decode(labels, skip_special_tokens=True)
+
+    print("Decoded predictions:", decoded_preds)
+    print("Decoded labels:", decoded_labels)
+
+    # Some simple post-processing
+    decoded_preds, decoded_labels = postprocess_text(decoded_preds, decoded_labels)
+
+    score = average_normalized_levenshtein_similarity(decoded_labels, decoded_preds)
+    result = {"levenshtein": score}
+
+    prediction_lens = [np.count_nonzero(pred != processor.tokenizer.pad_token_id) for pred in preds]
+    result["gen_len"] = np.mean(prediction_lens)
+    result = {k: round(v, 4) for k, v in result.items()}
+    return result
+
+
+# def compute_metrics(eval_preds):
+#     # Get the predicted and ground truth token sequences
+#     # These are lists as they have different shapes for each batch
+#     # We explicitly pass `eval_do_concat_batches=False` to the trainer
+#     # TODO we could also just pad the input_ids/labels in the data collator
+#     preds, labels = eval_preds
+
+#     final_preds = []
+#     final_labels = []
+#     for batch_pred, batch_label in zip(preds, labels):
+#         if isinstance(batch_pred, tuple):
+#             batch_pred = batch_pred[0]
+
+#         # Decode the generated ids and labels
+#         decoded_preds = processor.batch_decode(batch_pred, skip_special_tokens=True)
+#         decoded_labels = processor.batch_decode(batch_label, skip_special_tokens=True)
+
+#         # Some simple post-processing
+#         decoded_preds, decoded_labels = postprocess_text(decoded_preds, decoded_labels)
+
+#         final_preds.extend(decoded_preds)
+#         final_labels.extend(decoded_labels)
+
+#     N = len(final_labels)
+#     total_score = 0
+
+#     for i in range(N):
+#         a_i = final_labels[i]
+#         o_q_i = final_preds[i]
+#         if o_q_i == "":
+#             print("Warning: Skipped an empty prediction.")
+#             max_score = 0
+#         else:
+#             max_score = max(similarity_score(a_ij, o_q_i) for a_ij in a_i)
+
+#         total_score += max_score
+
+#     return {"levenshtein": total_score / N}
+
+
+## Define Training Arguments and Trainer
+
+generation_config = GenerationConfig.from_pretrained("HuggingFaceM4/idefics2-8b", max_new_tokens=500)
+
+training_args = Seq2SeqTrainingArguments(
+    num_train_epochs=2,
+    per_device_train_batch_size=2,
+    per_device_eval_batch_size=8,
+    gradient_accumulation_steps=8,
+    warmup_steps=50,
+    learning_rate=1e-4,
+    weight_decay=0.01,
+    logging_steps=25,
+    output_dir="idefics2_ft_tutorial",
+    eval_strategy="epoch",
+    save_strategy="steps",
+    save_steps=250,
+    save_total_limit=1,
+    # evaluation_strategy="epoch",
+    fp16=True,
+    # push_to_hub_model_id="idefics2-8b-docvqa-finetuned-tutorial",
+    remove_unused_columns=False,
+    report_to="none",
+    # eval_do_concat_batches=False,
+    predict_with_generate=True,
+    generation_config=generation_config,
+)
+
+# important: we need to disable caching during training
+# otherwise the model generates past_key_values which is of type DynamicCache
+model.config.use_cache = False
+
+
+class Idefics2Trainer(Seq2SeqTrainer):
+    def prediction_step(
+        self,
+        model: nn.Module,
+        inputs: Dict[str, Union[torch.Tensor, Any]],
+        prediction_loss_only: bool,
+        ignore_keys: Optional[List[str]] = None,
+        **gen_kwargs,
+    ) -> Tuple[Optional[float], Optional[torch.Tensor], Optional[torch.Tensor]]:
+        """
+        Perform an evaluation step on `model` using `inputs`.
+
+        Subclass and override to inject custom behavior.
+
+        Args:
+            model (`nn.Module`):
+                The model to evaluate.
+            inputs (`Dict[str, Union[torch.Tensor, Any]]`):
+                The inputs and targets of the model.
+
+                The dictionary will be unpacked before being fed to the model. Most models expect the targets under the
+                argument `labels`. Check your model's documentation for all accepted arguments.
+            prediction_loss_only (`bool`):
+                Whether or not to return the loss only.
+            gen_kwargs:
+                Additional `generate` specific kwargs.
+
+        Return:
+            Tuple[Optional[float], Optional[torch.Tensor], Optional[torch.Tensor]]: A tuple with the loss, logits and
+            labels (each being optional).
+        """
+        if not self.args.predict_with_generate or prediction_loss_only:
+            return super().prediction_step(
+                model, inputs, prediction_loss_only=prediction_loss_only, ignore_keys=ignore_keys
+            )
+
+        has_labels = "labels" in inputs
+        inputs = self._prepare_inputs(inputs)
+
+        # Priority (handled in generate):
+        # non-`None` gen_kwargs > model.generation_config > default GenerationConfig()
+        if len(gen_kwargs) == 0 and hasattr(self, "_gen_kwargs"):
+            gen_kwargs = self._gen_kwargs.copy()
+        if "num_beams" in gen_kwargs and gen_kwargs["num_beams"] is None:
+            gen_kwargs.pop("num_beams")
+        if "max_length" in gen_kwargs and gen_kwargs["max_length"] is None:
+            gen_kwargs.pop("max_length")
+
+        default_synced_gpus = False
+        gen_kwargs["synced_gpus"] = (
+            gen_kwargs["synced_gpus"] if gen_kwargs.get("synced_gpus") is not None else default_synced_gpus
+        )
+
+        generation_inputs = inputs.copy()
+        # If the `decoder_input_ids` was created from `labels`, evict the former, so that the model can freely generate
+        # (otherwise, it would continue generating from the padded `decoder_input_ids`)
+        if (
+            "labels" in generation_inputs
+            and "decoder_input_ids" in generation_inputs
+            and generation_inputs["labels"].shape == generation_inputs["decoder_input_ids"].shape
+        ):
+            generation_inputs = {
+                k: v for k, v in inputs.items() if k not in ("decoder_input_ids", "decoder_attention_mask")
+            }
+
+        # here we need to overwrite the input_ids to only include the prompt
+        processor = AutoProcessor.from_pretrained("HuggingFaceM4/idefics2-8b", do_image_splitting=False)
+
+        # use dummy image
+        # we can do this since each image is always turned into 64 image tokens
+        url = "https://upload.wikimedia.org/wikipedia/commons/f/f3/Zinedine_Zidane_by_Tasnim_03.jpg"
+        test_image = Image.open(requests.get(url, stream=True).raw)
+
+        # prepare prompt for the model
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "Extract JSON."},
+                    {"type": "image"},
+                ],
+            },
+        ]
+        prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
+        processor_inputs = processor(text=prompt, images=[test_image], return_tensors="pt")
+        custom_inputs = {}
+        batch_size = generation_inputs["pixel_values"].shape[0]
+        device = generation_inputs["pixel_values"].device
+        custom_inputs["input_ids"] = processor_inputs.input_ids.repeat(batch_size, 1).to(
+            device
+        )  # repeat along batch dimension
+        custom_inputs["attention_mask"] = processor_inputs.attention_mask.repeat(batch_size, 1).to(
+            device
+        )  # repeat along batch dimension
+        custom_inputs["pixel_values"] = generation_inputs["pixel_values"]
+        custom_inputs["pixel_attention_mask"] = generation_inputs["pixel_attention_mask"]
+
+        # print("Custom inputs:")
+        # for k,v in custom_inputs.items():
+        #     if isinstance(v, torch.Tensor):
+        #         print(k,v.shape)
+
+        generated_tokens = self.model.generate(**custom_inputs, **gen_kwargs)
+
+        # Strip the prompt from the generated_tokens
+        generated_tokens = generated_tokens[:, custom_inputs["input_ids"].size(1) :]
+
+        # Temporary hack to ensure the generation config is not initialized for each iteration of the evaluation loop
+        # TODO: remove this hack when the legacy code that initializes generation_config from a model config is
+        # removed in https://github.com/huggingface/transformers/blob/98d88b23f54e5a23e741833f1e973fdf600cc2c5/src/transformers/generation/utils.py#L1183
+        if self.model.generation_config._from_model_config:
+            self.model.generation_config._from_model_config = False
+
+        # Retrieves GenerationConfig from model.generation_config
+        gen_config = self.model.generation_config
+        # in case the batch is shorter than max length, the output should be padded
+        if generated_tokens.shape[-1] < gen_config.max_length:
+            generated_tokens = self._pad_tensors_to_max_len(generated_tokens, gen_config.max_length)
+        elif gen_config.max_new_tokens is not None and generated_tokens.shape[-1] < gen_config.max_new_tokens + 1:
+            generated_tokens = self._pad_tensors_to_max_len(generated_tokens, gen_config.max_new_tokens + 1)
+
+        with torch.no_grad():
+            if has_labels:
+                with self.compute_loss_context_manager():
+                    outputs = model(**inputs)
+                if self.label_smoother is not None:
+                    loss = self.label_smoother(outputs, inputs["labels"]).mean().detach()
+                else:
+                    loss = (outputs["loss"] if isinstance(outputs, dict) else outputs[0]).mean().detach()
+            else:
+                loss = None
+
+        if self.args.prediction_loss_only:
+            return loss, None, None
+
+        if has_labels:
+            labels = inputs["labels"]
+            if labels.shape[-1] < gen_config.max_length:
+                labels = self._pad_tensors_to_max_len(labels, gen_config.max_length)
+            elif gen_config.max_new_tokens is not None and labels.shape[-1] < gen_config.max_new_tokens + 1:
+                labels = self._pad_tensors_to_max_len(labels, gen_config.max_new_tokens + 1)
+        else:
+            labels = None
+
+        return loss, generated_tokens, labels
+
+    def _pad_tensors_to_max_len(self, tensor, max_length):
+        pad_token_id = processor.tokenizer.pad_token_id
+
+        padded_tensor = pad_token_id * torch.ones(
+            (tensor.shape[0], max_length), dtype=tensor.dtype, device=tensor.device
+        )
+        padded_tensor[:, : tensor.shape[-1]] = tensor
+        return padded_tensor
+
+
+trainer = Idefics2Trainer(
+    model=model,
+    args=training_args,
+    data_collator=data_collator,
+    train_dataset=train_dataset,
+    eval_dataset=eval_dataset,
+    compute_metrics=compute_metrics,
+)
+
+trainer.train()
diff --git a/src/transformers/models/idefics2/fine_tune_idefics2_pl.ipynb b/src/transformers/models/idefics2/fine_tune_idefics2_pl.ipynb
new file mode 100644
index 00000000000000..5541a2e6b2e9b8
--- /dev/null
+++ b/src/transformers/models/idefics2/fine_tune_idefics2_pl.ipynb
@@ -0,0 +1,970 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/niels/python_projects/transformers/env/lib/python3.8/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset\n",
+    "\n",
+    "dataset = load_dataset(\"naver-clova-ix/cord-v2\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "DatasetDict({\n",
+       "    train: Dataset({\n",
+       "        features: ['image', 'ground_truth'],\n",
+       "        num_rows: 800\n",
+       "    })\n",
+       "    validation: Dataset({\n",
+       "        features: ['image', 'ground_truth'],\n",
+       "        num_rows: 100\n",
+       "    })\n",
+       "    test: Dataset({\n",
+       "        features: ['image', 'ground_truth'],\n",
+       "        num_rows: 100\n",
+       "    })\n",
+       "})"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dataset"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's take a look at the first training example:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/jpeg": "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",
+      "image/png": "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",
+      "text/plain": [
+       "<PIL.Image.Image image mode=RGB size=259x388>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "example = dataset['train'][0]\n",
+    "image = example['image']\n",
+    "# let's make the image a bit smaller when visualizing\n",
+    "width, height = image.size\n",
+    "display(image.resize((int(width*0.3), int(height*0.3))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\"gt_parse\": {\"menu\": [{\"nm\": \"Nasi Campur Bali\", \"cnt\": \"1 x\", \"price\": \"75,000\"}, {\"nm\": \"Bbk Bengil Nasi\", \"cnt\": \"1 x\", \"price\": \"125,000\"}, {\"nm\": \"MilkShake Starwb\", \"cnt\": \"1 x\", \"price\": \"37,000\"}, {\"nm\": \"Ice Lemon Tea\", \"cnt\": \"1 x\", \"price\": \"24,000\"}, {\"nm\": \"Nasi Ayam Dewata\", \"cnt\": \"1 x\", \"price\": \"70,000\"}, {\"nm\": \"Free Ice Tea\", \"cnt\": \"3 x\", \"price\": \"0\"}, {\"nm\": \"Organic Green Sa\", \"cnt\": \"1 x\", \"price\": \"65,000\"}, {\"nm\": \"Ice Tea\", \"cnt\": \"1 x\", \"price\": \"18,000\"}, {\"nm\": \"Ice Orange\", \"cnt\": \"1 x\", \"price\": \"29,000\"}, {\"nm\": \"Ayam Suir Bali\", \"cnt\": \"1 x\", \"price\": \"85,000\"}, {\"nm\": \"Tahu Goreng\", \"cnt\": \"2 x\", \"price\": \"36,000\"}, {\"nm\": \"Tempe Goreng\", \"cnt\": \"2 x\", \"price\": \"36,000\"}, {\"nm\": \"Tahu Telor Asin\", \"cnt\": \"1 x\", \"price\": \"40,000.\"}, {\"nm\": \"Nasi Goreng Samb\", \"cnt\": \"1 x\", \"price\": \"70,000\"}, {\"nm\": \"Bbk Panggang Sam\", \"cnt\": \"3 x\", \"price\": \"366,000\"}, {\"nm\": \"Ayam Sambal Hija\", \"cnt\": \"1 x\", \"price\": \"92,000\"}, {\"nm\": \"Hot Tea\", \"cnt\": \"2 x\", \"price\": \"44,000\"}, {\"nm\": \"Ice Kopi\", \"cnt\": \"1 x\", \"price\": \"32,000\"}, {\"nm\": \"Tahu Telor Asin\", \"cnt\": \"1 x\", \"price\": \"40,000\"}, {\"nm\": \"Free Ice Tea\", \"cnt\": \"1 x\", \"price\": \"0\"}, {\"nm\": \"Bebek Street\", \"cnt\": \"1 x\", \"price\": \"44,000\"}, {\"nm\": \"Ice Tea Tawar\", \"cnt\": \"1 x\", \"price\": \"18,000\"}], \"sub_total\": {\"subtotal_price\": \"1,346,000\", \"service_price\": \"100,950\", \"tax_price\": \"144,695\", \"etc\": \"-45\"}, \"total\": {\"total_price\": \"1,591,600\"}}, \"meta\": {\"version\": \"2.0.0\", \"split\": \"train\", \"image_id\": 0, \"image_size\": {\"width\": 864, \"height\": 1296}}, \"valid_line\": [{\"words\": [{\"quad\": {\"x2\": 244, \"y3\": 390, \"x3\": 244, \"y4\": 390, \"x1\": 232, \"y1\": 372, \"x4\": 232, \"y2\": 372}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"1\"}, {\"quad\": {\"x2\": 270, \"y3\": 390, \"x3\": 270, \"y4\": 390, \"x1\": 256, \"y1\": 374, \"x4\": 256, \"y2\": 374}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 3, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 354, \"y3\": 390, \"x3\": 354, \"y4\": 390, \"x1\": 302, \"y1\": 368, \"x4\": 302, \"y2\": 368}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"Nasi\"}, {\"quad\": {\"x2\": 440, \"y3\": 391, \"x3\": 439, \"y4\": 388, \"x1\": 364, \"y1\": 365, \"x4\": 363, \"y2\": 368}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"Campur\"}, {\"quad\": {\"x2\": 497, \"y3\": 385, \"x3\": 499, \"y4\": 388, \"x1\": 446, \"y1\": 365, \"x4\": 448, \"y2\": 362}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"Bali\"}], \"category\": \"menu.nm\", \"group_id\": 3, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 388, \"x3\": 618, \"y4\": 388, \"x1\": 542, \"y1\": 362, \"x4\": 542, \"y2\": 362}, \"is_key\": 0, \"row_id\": 2179893, \"text\": \"75,000\"}], \"category\": \"menu.price\", \"group_id\": 3, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 246, \"y3\": 418, \"x3\": 246, \"y4\": 418, \"x1\": 234, \"y1\": 400, \"x4\": 234, \"y2\": 400}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"1\"}, {\"quad\": {\"x2\": 270, \"y3\": 418, \"x3\": 270, \"y4\": 418, \"x1\": 258, \"y1\": 402, \"x4\": 258, \"y2\": 402}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 4, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 344, \"y3\": 418, \"x3\": 344, \"y4\": 418, \"x1\": 304, \"y1\": 394, \"x4\": 304, \"y2\": 394}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"Bbk\"}, {\"quad\": {\"x2\": 430, \"y3\": 418, \"x3\": 430, \"y4\": 418, \"x1\": 352, \"y1\": 394, \"x4\": 352, \"y2\": 394}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"Bengil\"}, {\"quad\": {\"x2\": 488, \"y3\": 414, \"x3\": 488, \"y4\": 414, \"x1\": 436, \"y1\": 392, \"x4\": 436, \"y2\": 392}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"Nasi\"}], \"category\": \"menu.nm\", \"group_id\": 4, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 414, \"x3\": 618, \"y4\": 414, \"x1\": 534, \"y1\": 388, \"x4\": 534, \"y2\": 388}, \"is_key\": 0, \"row_id\": 2179894, \"text\": \"125,000\"}], \"category\": \"menu.price\", \"group_id\": 4, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 246, \"y3\": 444, \"x3\": 246, \"y4\": 444, \"x1\": 234, \"y1\": 426, \"x4\": 234, \"y2\": 426}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"1\"}, {\"quad\": {\"x2\": 272, \"y3\": 444, \"x3\": 272, \"y4\": 444, \"x1\": 258, \"y1\": 428, \"x4\": 258, \"y2\": 428}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 5, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 417, \"y3\": 444, \"x3\": 417, \"y4\": 444, \"x1\": 303, \"y1\": 420, \"x4\": 303, \"y2\": 420}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"MilkShake\"}, {\"quad\": {\"x2\": 500, \"y3\": 440, \"x3\": 500, \"y4\": 440, \"x1\": 424, \"y1\": 418, \"x4\": 424, \"y2\": 418}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"Starwb\"}], \"category\": \"menu.nm\", \"group_id\": 5, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 440, \"x3\": 620, \"y4\": 440, \"x1\": 544, \"y1\": 414, \"x4\": 544, \"y2\": 414}, \"is_key\": 0, \"row_id\": 2179895, \"text\": \"37,000\"}], \"category\": \"menu.price\", \"group_id\": 5, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 248, \"y3\": 470, \"x3\": 248, \"y4\": 470, \"x1\": 236, \"y1\": 452, \"x4\": 236, \"y2\": 452}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"1\"}, {\"quad\": {\"x2\": 274, \"y3\": 470, \"x3\": 274, \"y4\": 470, \"x1\": 260, \"y1\": 456, \"x4\": 260, \"y2\": 456}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 6, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 348, \"y3\": 470, \"x3\": 348, \"y4\": 470, \"x1\": 306, \"y1\": 448, \"x4\": 306, \"y2\": 448}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 418, \"y3\": 468, \"x3\": 418, \"y4\": 468, \"x1\": 354, \"y1\": 446, \"x4\": 354, \"y2\": 446}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"Lemon\"}, {\"quad\": {\"x2\": 466, \"y3\": 466, \"x3\": 466, \"y4\": 466, \"x1\": 426, \"y1\": 446, \"x4\": 426, \"y2\": 446}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 6, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 466, \"x3\": 618, \"y4\": 466, \"x1\": 544, \"y1\": 440, \"x4\": 544, \"y2\": 440}, \"is_key\": 0, \"row_id\": 2179896, \"text\": \"24,000\"}], \"category\": \"menu.price\", \"group_id\": 6, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 496, \"x3\": 250, \"y4\": 496, \"x1\": 238, \"y1\": 480, \"x4\": 238, \"y2\": 480}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"1\"}, {\"quad\": {\"x2\": 274, \"y3\": 496, \"x3\": 274, \"y4\": 496, \"x1\": 258, \"y1\": 480, \"x4\": 258, \"y2\": 480}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 7, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 358, \"y3\": 496, \"x3\": 358, \"y4\": 496, \"x1\": 306, \"y1\": 474, \"x4\": 306, \"y2\": 474}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"Nasi\"}, {\"quad\": {\"x2\": 420, \"y3\": 496, \"x3\": 420, \"y4\": 496, \"x1\": 366, \"y1\": 474, \"x4\": 366, \"y2\": 474}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"Ayam\"}, {\"quad\": {\"x2\": 499, \"y3\": 491, \"x3\": 500, \"y4\": 494, \"x1\": 425, \"y1\": 471, \"x4\": 426, \"y2\": 469}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"Dewata\"}], \"category\": \"menu.nm\", \"group_id\": 7, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 492, \"x3\": 618, \"y4\": 492, \"x1\": 544, \"y1\": 466, \"x4\": 544, \"y2\": 466}, \"is_key\": 0, \"row_id\": 2179897, \"text\": \"70,000\"}], \"category\": \"menu.price\", \"group_id\": 7, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 252, \"y3\": 522, \"x3\": 252, \"y4\": 522, \"x1\": 240, \"y1\": 504, \"x4\": 240, \"y2\": 504}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"3\"}, {\"quad\": {\"x2\": 276, \"y3\": 522, \"x3\": 276, \"y4\": 522, \"x1\": 260, \"y1\": 506, \"x4\": 260, \"y2\": 506}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 8, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 360, \"y3\": 522, \"x3\": 360, \"y4\": 522, \"x1\": 306, \"y1\": 500, \"x4\": 306, \"y2\": 500}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"Free\"}, {\"quad\": {\"x2\": 408, \"y3\": 522, \"x3\": 408, \"y4\": 522, \"x1\": 368, \"y1\": 500, \"x4\": 368, \"y2\": 500}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 454, \"y3\": 520, \"x3\": 454, \"y4\": 520, \"x1\": 416, \"y1\": 498, \"x4\": 416, \"y2\": 498}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 8, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 514, \"x3\": 618, \"y4\": 514, \"x1\": 604, \"y1\": 494, \"x4\": 604, \"y2\": 494}, \"is_key\": 0, \"row_id\": 2179898, \"text\": \"0\"}], \"category\": \"menu.price\", \"group_id\": 8, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 546, \"x3\": 254, \"y4\": 546, \"x1\": 242, \"y1\": 530, \"x4\": 242, \"y2\": 530}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"1\"}, {\"quad\": {\"x2\": 278, \"y3\": 548, \"x3\": 278, \"y4\": 548, \"x1\": 262, \"y1\": 532, \"x4\": 262, \"y2\": 532}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 9, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 396, \"y3\": 548, \"x3\": 396, \"y4\": 548, \"x1\": 308, \"y1\": 526, \"x4\": 308, \"y2\": 526}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"Organic\"}, {\"quad\": {\"x2\": 466, \"y3\": 544, \"x3\": 466, \"y4\": 544, \"x1\": 404, \"y1\": 524, \"x4\": 404, \"y2\": 524}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"Green\"}, {\"quad\": {\"x2\": 502, \"y3\": 544, \"x3\": 502, \"y4\": 544, \"x1\": 474, \"y1\": 522, \"x4\": 474, \"y2\": 522}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"Sa\"}], \"category\": \"menu.nm\", \"group_id\": 9, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 542, \"x3\": 620, \"y4\": 542, \"x1\": 544, \"y1\": 518, \"x4\": 544, \"y2\": 518}, \"is_key\": 0, \"row_id\": 2179899, \"text\": \"65,000\"}], \"category\": \"menu.price\", \"group_id\": 9, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 572, \"x3\": 254, \"y4\": 572, \"x1\": 242, \"y1\": 556, \"x4\": 242, \"y2\": 556}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"1\"}, {\"quad\": {\"x2\": 280, \"y3\": 572, \"x3\": 280, \"y4\": 572, \"x1\": 266, \"y1\": 558, \"x4\": 266, \"y2\": 558}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 10, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 572, \"x3\": 352, \"y4\": 572, \"x1\": 312, \"y1\": 552, \"x4\": 312, \"y2\": 552}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 398, \"y3\": 572, \"x3\": 398, \"y4\": 572, \"x1\": 358, \"y1\": 550, \"x4\": 358, \"y2\": 550}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 10, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 568, \"x3\": 620, \"y4\": 568, \"x1\": 546, \"y1\": 544, \"x4\": 546, \"y2\": 544}, \"is_key\": 0, \"row_id\": 2179900, \"text\": \"18,000\"}], \"category\": \"menu.price\", \"group_id\": 10, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 256, \"y3\": 598, \"x3\": 256, \"y4\": 598, \"x1\": 244, \"y1\": 582, \"x4\": 244, \"y2\": 582}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"1\"}, {\"quad\": {\"x2\": 280, \"y3\": 598, \"x3\": 280, \"y4\": 598, \"x1\": 264, \"y1\": 582, \"x4\": 264, \"y2\": 582}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 11, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 596, \"x3\": 352, \"y4\": 596, \"x1\": 312, \"y1\": 576, \"x4\": 312, \"y2\": 576}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 434, \"y3\": 596, \"x3\": 434, \"y4\": 596, \"x1\": 358, \"y1\": 576, \"x4\": 358, \"y2\": 576}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"Orange\"}], \"category\": \"menu.nm\", \"group_id\": 11, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 594, \"x3\": 620, \"y4\": 594, \"x1\": 544, \"y1\": 570, \"x4\": 544, \"y2\": 570}, \"is_key\": 0, \"row_id\": 2179901, \"text\": \"29,000\"}], \"category\": \"menu.price\", \"group_id\": 11, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 258, \"y3\": 622, \"x3\": 258, \"y4\": 622, \"x1\": 246, \"y1\": 606, \"x4\": 246, \"y2\": 606}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"1\"}, {\"quad\": {\"x2\": 282, \"y3\": 622, \"x3\": 282, \"y4\": 622, \"x1\": 268, \"y1\": 608, \"x4\": 268, \"y2\": 608}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 12, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 624, \"x3\": 364, \"y4\": 624, \"x1\": 312, \"y1\": 602, \"x4\": 312, \"y2\": 602}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"Ayam\"}, {\"quad\": {\"x2\": 422, \"y3\": 620, \"x3\": 422, \"y4\": 620, \"x1\": 370, \"y1\": 600, \"x4\": 370, \"y2\": 600}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"Suir\"}, {\"quad\": {\"x2\": 478, \"y3\": 620, \"x3\": 478, \"y4\": 620, \"x1\": 428, \"y1\": 598, \"x4\": 428, \"y2\": 598}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"Bali\"}], \"category\": \"menu.nm\", \"group_id\": 12, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 618, \"y3\": 620, \"x3\": 618, \"y4\": 620, \"x1\": 544, \"y1\": 596, \"x4\": 544, \"y2\": 596}, \"is_key\": 0, \"row_id\": 2179902, \"text\": \"85,000\"}], \"category\": \"menu.price\", \"group_id\": 12, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 260, \"y3\": 650, \"x3\": 260, \"y4\": 650, \"x1\": 242, \"y1\": 628, \"x4\": 242, \"y2\": 628}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"2\"}, {\"quad\": {\"x2\": 282, \"y3\": 648, \"x3\": 282, \"y4\": 648, \"x1\": 266, \"y1\": 632, \"x4\": 266, \"y2\": 632}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 13, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 648, \"x3\": 364, \"y4\": 648, \"x1\": 312, \"y1\": 626, \"x4\": 312, \"y2\": 626}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"Tahu\"}, {\"quad\": {\"x2\": 444, \"y3\": 648, \"x3\": 443, \"y4\": 645, \"x1\": 370, \"y1\": 625, \"x4\": 369, \"y2\": 628}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"Goreng\"}], \"category\": \"menu.nm\", \"group_id\": 13, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 619, \"y3\": 644, \"x3\": 620, \"y4\": 647, \"x1\": 543, \"y1\": 622, \"x4\": 544, \"y2\": 619}, \"is_key\": 0, \"row_id\": 2179903, \"text\": \"36,000\"}], \"category\": \"menu.price\", \"group_id\": 13, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 260, \"y3\": 674, \"x3\": 260, \"y4\": 674, \"x1\": 242, \"y1\": 654, \"x4\": 242, \"y2\": 654}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"2\"}, {\"quad\": {\"x2\": 284, \"y3\": 674, \"x3\": 284, \"y4\": 674, \"x1\": 268, \"y1\": 660, \"x4\": 268, \"y2\": 660}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 14, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 376, \"y3\": 674, \"x3\": 376, \"y4\": 674, \"x1\": 314, \"y1\": 652, \"x4\": 314, \"y2\": 652}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"Tempe\"}, {\"quad\": {\"x2\": 458, \"y3\": 672, \"x3\": 458, \"y4\": 672, \"x1\": 384, \"y1\": 650, \"x4\": 384, \"y2\": 650}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"Goreng\"}], \"category\": \"menu.nm\", \"group_id\": 14, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 620, \"y3\": 668, \"x3\": 620, \"y4\": 668, \"x1\": 546, \"y1\": 644, \"x4\": 546, \"y2\": 644}, \"is_key\": 0, \"row_id\": 2179904, \"text\": \"36,000\"}], \"category\": \"menu.price\", \"group_id\": 14, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 258, \"y3\": 700, \"x3\": 258, \"y4\": 700, \"x1\": 244, \"y1\": 682, \"x4\": 244, \"y2\": 682}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"1\"}, {\"quad\": {\"x2\": 282, \"y3\": 700, \"x3\": 282, \"y4\": 700, \"x1\": 266, \"y1\": 686, \"x4\": 266, \"y2\": 686}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 15, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 698, \"x3\": 364, \"y4\": 698, \"x1\": 312, \"y1\": 676, \"x4\": 312, \"y2\": 676}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"Tahu\"}, {\"quad\": {\"x2\": 434, \"y3\": 696, \"x3\": 434, \"y4\": 696, \"x1\": 370, \"y1\": 674, \"x4\": 370, \"y2\": 674}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"Telor\"}, {\"quad\": {\"x2\": 494, \"y3\": 694, \"x3\": 494, \"y4\": 694, \"x1\": 440, \"y1\": 672, \"x4\": 440, \"y2\": 672}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"Asin\"}], \"category\": \"menu.nm\", \"group_id\": 15, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 630, \"y3\": 690, \"x3\": 630, \"y4\": 690, \"x1\": 548, \"y1\": 668, \"x4\": 548, \"y2\": 668}, \"is_key\": 0, \"row_id\": 2179905, \"text\": \"40,000.\"}], \"category\": \"menu.price\", \"group_id\": 15, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 256, \"y3\": 726, \"x3\": 256, \"y4\": 726, \"x1\": 244, \"y1\": 708, \"x4\": 244, \"y2\": 708}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"1\"}, {\"quad\": {\"x2\": 282, \"y3\": 726, \"x3\": 282, \"y4\": 726, \"x1\": 268, \"y1\": 710, \"x4\": 268, \"y2\": 710}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 16, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 724, \"x3\": 364, \"y4\": 724, \"x1\": 312, \"y1\": 702, \"x4\": 312, \"y2\": 702}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"Nasi\"}, {\"quad\": {\"x2\": 446, \"y3\": 722, \"x3\": 446, \"y4\": 722, \"x1\": 372, \"y1\": 700, \"x4\": 372, \"y2\": 700}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"Goreng\"}, {\"quad\": {\"x2\": 505, \"y3\": 715, \"x3\": 506, \"y4\": 718, \"x1\": 453, \"y1\": 696, \"x4\": 454, \"y2\": 693}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"Samb\"}], \"category\": \"menu.nm\", \"group_id\": 16, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 626, \"y3\": 716, \"x3\": 626, \"y4\": 716, \"x1\": 550, \"y1\": 692, \"x4\": 550, \"y2\": 692}, \"is_key\": 0, \"row_id\": 2179906, \"text\": \"70,000\"}], \"category\": \"menu.price\", \"group_id\": 16, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 256, \"y3\": 752, \"x3\": 256, \"y4\": 752, \"x1\": 242, \"y1\": 734, \"x4\": 242, \"y2\": 734}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"3\"}, {\"quad\": {\"x2\": 280, \"y3\": 752, \"x3\": 280, \"y4\": 752, \"x1\": 266, \"y1\": 738, \"x4\": 266, \"y2\": 738}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 17, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 750, \"x3\": 352, \"y4\": 750, \"x1\": 312, \"y1\": 728, \"x4\": 312, \"y2\": 728}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"Bbk\"}, {\"quad\": {\"x2\": 457, \"y3\": 747, \"x3\": 458, \"y4\": 749, \"x1\": 357, \"y1\": 726, \"x4\": 358, \"y2\": 723}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"Panggang\"}, {\"quad\": {\"x2\": 508, \"y3\": 742, \"x3\": 508, \"y4\": 742, \"x1\": 466, \"y1\": 722, \"x4\": 466, \"y2\": 722}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"Sam\"}], \"category\": \"menu.nm\", \"group_id\": 17, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 630, \"y3\": 742, \"x3\": 630, \"y4\": 742, \"x1\": 538, \"y1\": 716, \"x4\": 538, \"y2\": 716}, \"is_key\": 0, \"row_id\": 2179907, \"text\": \"366,000\"}], \"category\": \"menu.price\", \"group_id\": 17, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 778, \"x3\": 254, \"y4\": 778, \"x1\": 242, \"y1\": 762, \"x4\": 242, \"y2\": 762}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"1\"}, {\"quad\": {\"x2\": 280, \"y3\": 778, \"x3\": 280, \"y4\": 778, \"x1\": 266, \"y1\": 764, \"x4\": 266, \"y2\": 764}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 18, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 778, \"x3\": 364, \"y4\": 778, \"x1\": 312, \"y1\": 754, \"x4\": 312, \"y2\": 754}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"Ayam\"}, {\"quad\": {\"x2\": 447, \"y3\": 771, \"x3\": 448, \"y4\": 774, \"x1\": 371, \"y1\": 750, \"x4\": 372, \"y2\": 747}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"Sambal\"}, {\"quad\": {\"x2\": 508, \"y3\": 772, \"x3\": 508, \"y4\": 772, \"x1\": 454, \"y1\": 746, \"x4\": 454, \"y2\": 746}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"Hija\"}], \"category\": \"menu.nm\", \"group_id\": 18, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 632, \"y3\": 768, \"x3\": 632, \"y4\": 768, \"x1\": 554, \"y1\": 742, \"x4\": 554, \"y2\": 742}, \"is_key\": 0, \"row_id\": 2179908, \"text\": \"92,000\"}], \"category\": \"menu.price\", \"group_id\": 18, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 254, \"y3\": 806, \"x3\": 254, \"y4\": 806, \"x1\": 236, \"y1\": 784, \"x4\": 236, \"y2\": 784}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"2\"}, {\"quad\": {\"x2\": 278, \"y3\": 804, \"x3\": 278, \"y4\": 804, \"x1\": 262, \"y1\": 788, \"x4\": 262, \"y2\": 788}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 19, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 802, \"x3\": 352, \"y4\": 802, \"x1\": 310, \"y1\": 780, \"x4\": 310, \"y2\": 780}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"Hot\"}, {\"quad\": {\"x2\": 400, \"y3\": 800, \"x3\": 400, \"y4\": 800, \"x1\": 358, \"y1\": 778, \"x4\": 358, \"y2\": 778}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 19, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 634, \"y3\": 796, \"x3\": 634, \"y4\": 796, \"x1\": 554, \"y1\": 770, \"x4\": 554, \"y2\": 770}, \"is_key\": 0, \"row_id\": 2179909, \"text\": \"44,000\"}], \"category\": \"menu.price\", \"group_id\": 19, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 252, \"y3\": 834, \"x3\": 252, \"y4\": 834, \"x1\": 240, \"y1\": 816, \"x4\": 240, \"y2\": 816}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"1\"}, {\"quad\": {\"x2\": 278, \"y3\": 832, \"x3\": 278, \"y4\": 832, \"x1\": 262, \"y1\": 816, \"x4\": 262, \"y2\": 816}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 20, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 830, \"x3\": 352, \"y4\": 830, \"x1\": 312, \"y1\": 808, \"x4\": 312, \"y2\": 808}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 412, \"y3\": 830, \"x3\": 412, \"y4\": 830, \"x1\": 360, \"y1\": 804, \"x4\": 360, \"y2\": 804}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"Kopi\"}], \"category\": \"menu.nm\", \"group_id\": 20, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 636, \"y3\": 826, \"x3\": 636, \"y4\": 826, \"x1\": 556, \"y1\": 798, \"x4\": 556, \"y2\": 798}, \"is_key\": 0, \"row_id\": 2179910, \"text\": \"32,000\"}], \"category\": \"menu.price\", \"group_id\": 20, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 862, \"x3\": 250, \"y4\": 862, \"x1\": 238, \"y1\": 844, \"x4\": 238, \"y2\": 844}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 862, \"x3\": 276, \"y4\": 862, \"x1\": 260, \"y1\": 844, \"x4\": 260, \"y2\": 844}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 21, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 860, \"x3\": 364, \"y4\": 860, \"x1\": 310, \"y1\": 836, \"x4\": 310, \"y2\": 836}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"Tahu\"}, {\"quad\": {\"x2\": 438, \"y3\": 858, \"x3\": 438, \"y4\": 858, \"x1\": 372, \"y1\": 834, \"x4\": 372, \"y2\": 834}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"Telor\"}, {\"quad\": {\"x2\": 500, \"y3\": 854, \"x3\": 500, \"y4\": 854, \"x1\": 444, \"y1\": 832, \"x4\": 444, \"y2\": 832}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"Asin\"}], \"category\": \"menu.nm\", \"group_id\": 21, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 638, \"y3\": 854, \"x3\": 638, \"y4\": 854, \"x1\": 558, \"y1\": 826, \"x4\": 558, \"y2\": 826}, \"is_key\": 0, \"row_id\": 2179911, \"text\": \"40,000\"}], \"category\": \"menu.price\", \"group_id\": 21, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 892, \"x3\": 250, \"y4\": 892, \"x1\": 238, \"y1\": 872, \"x4\": 238, \"y2\": 872}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 890, \"x3\": 276, \"y4\": 890, \"x1\": 260, \"y1\": 872, \"x4\": 260, \"y2\": 872}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 22, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 364, \"y3\": 888, \"x3\": 364, \"y4\": 888, \"x1\": 310, \"y1\": 866, \"x4\": 310, \"y2\": 866}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"Free\"}, {\"quad\": {\"x2\": 414, \"y3\": 886, \"x3\": 414, \"y4\": 886, \"x1\": 374, \"y1\": 864, \"x4\": 374, \"y2\": 864}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 464, \"y3\": 884, \"x3\": 464, \"y4\": 884, \"x1\": 422, \"y1\": 862, \"x4\": 422, \"y2\": 862}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"Tea\"}], \"category\": \"menu.nm\", \"group_id\": 22, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 640, \"y3\": 878, \"x3\": 640, \"y4\": 878, \"x1\": 622, \"y1\": 856, \"x4\": 622, \"y2\": 856}, \"is_key\": 0, \"row_id\": 2179912, \"text\": \"0\"}], \"category\": \"menu.price\", \"group_id\": 22, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 920, \"x3\": 250, \"y4\": 920, \"x1\": 236, \"y1\": 900, \"x4\": 236, \"y2\": 900}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 920, \"x3\": 276, \"y4\": 920, \"x1\": 260, \"y1\": 902, \"x4\": 260, \"y2\": 902}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 23, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 376, \"y3\": 916, \"x3\": 376, \"y4\": 916, \"x1\": 308, \"y1\": 892, \"x4\": 308, \"y2\": 892}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"Bebek\"}, {\"quad\": {\"x2\": 464, \"y3\": 914, \"x3\": 464, \"y4\": 914, \"x1\": 384, \"y1\": 890, \"x4\": 384, \"y2\": 890}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"Street\"}], \"category\": \"menu.nm\", \"group_id\": 23, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 641, \"y3\": 908, \"x3\": 642, \"y4\": 911, \"x1\": 559, \"y1\": 884, \"x4\": 560, \"y2\": 881}, \"is_key\": 0, \"row_id\": 2179913, \"text\": \"44,000\"}], \"category\": \"menu.price\", \"group_id\": 23, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 250, \"y3\": 948, \"x3\": 250, \"y4\": 948, \"x1\": 238, \"y1\": 930, \"x4\": 238, \"y2\": 930}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"1\"}, {\"quad\": {\"x2\": 276, \"y3\": 946, \"x3\": 276, \"y4\": 946, \"x1\": 260, \"y1\": 930, \"x4\": 260, \"y2\": 930}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"x\"}], \"category\": \"menu.cnt\", \"group_id\": 24, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 352, \"y3\": 946, \"x3\": 352, \"y4\": 946, \"x1\": 312, \"y1\": 924, \"x4\": 312, \"y2\": 924}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"Ice\"}, {\"quad\": {\"x2\": 402, \"y3\": 944, \"x3\": 402, \"y4\": 944, \"x1\": 360, \"y1\": 922, \"x4\": 360, \"y2\": 922}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"Tea\"}, {\"quad\": {\"x2\": 480, \"y3\": 942, \"x3\": 480, \"y4\": 942, \"x1\": 412, \"y1\": 920, \"x4\": 412, \"y2\": 920}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"Tawar\"}], \"category\": \"menu.nm\", \"group_id\": 24, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 642, \"y3\": 938, \"x3\": 642, \"y4\": 938, \"x1\": 564, \"y1\": 912, \"x4\": 564, \"y2\": 912}, \"is_key\": 0, \"row_id\": 2179914, \"text\": \"18,000\"}], \"category\": \"menu.price\", \"group_id\": 24, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 479, \"y3\": 998, \"x3\": 481, \"y4\": 1005, \"x1\": 360, \"y1\": 979, \"x4\": 362, \"y2\": 973}, \"is_key\": 1, \"row_id\": 2179915, \"text\": \"Sub-Total\"}, {\"quad\": {\"x2\": 645, \"y3\": 995, \"x3\": 646, \"y4\": 998, \"x1\": 527, \"y1\": 970, \"x4\": 528, \"y2\": 967}, \"is_key\": 0, \"row_id\": 2179915, \"text\": \"1,346,000\"}], \"category\": \"sub_total.subtotal_price\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 481, \"y3\": 1027, \"x3\": 482, \"y4\": 1030, \"x1\": 387, \"y1\": 1007, \"x4\": 388, \"y2\": 1004}, \"is_key\": 1, \"row_id\": 2179916, \"text\": \"Service\"}, {\"quad\": {\"x2\": 646, \"y3\": 1026, \"x3\": 646, \"y4\": 1026, \"x1\": 554, \"y1\": 998, \"x4\": 554, \"y2\": 998}, \"is_key\": 0, \"row_id\": 2179916, \"text\": \"100,950\"}], \"category\": \"sub_total.service_price\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 482, \"y3\": 1056, \"x3\": 482, \"y4\": 1056, \"x1\": 438, \"y1\": 1032, \"x4\": 438, \"y2\": 1032}, \"is_key\": 1, \"row_id\": 2179917, \"text\": \"PB1\"}, {\"quad\": {\"x2\": 648, \"y3\": 1052, \"x3\": 648, \"y4\": 1052, \"x1\": 556, \"y1\": 1026, \"x4\": 556, \"y2\": 1026}, \"is_key\": 0, \"row_id\": 2179917, \"text\": \"144,695\"}], \"category\": \"sub_total.tax_price\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 481, \"y3\": 1085, \"x3\": 482, \"y4\": 1088, \"x1\": 375, \"y1\": 1063, \"x4\": 376, \"y2\": 1061}, \"is_key\": 1, \"row_id\": 2179918, \"text\": \"Rounding\"}, {\"quad\": {\"x2\": 648, \"y3\": 1078, \"x3\": 648, \"y4\": 1078, \"x1\": 606, \"y1\": 1054, \"x4\": 606, \"y2\": 1054}, \"is_key\": 0, \"row_id\": 2179918, \"text\": \"-45\"}], \"category\": \"sub_total.etc\", \"group_id\": 25, \"sub_group_id\": 0}, {\"words\": [{\"quad\": {\"x2\": 334, \"y3\": 1162, \"x3\": 334, \"y4\": 1162, \"x1\": 266, \"y1\": 1142, \"x4\": 266, \"y2\": 1142}, \"is_key\": 1, \"row_id\": 2179919, \"text\": \"Grand\"}, {\"quad\": {\"x2\": 408, \"y3\": 1160, \"x3\": 408, \"y4\": 1160, \"x1\": 340, \"y1\": 1138, \"x4\": 340, \"y2\": 1138}, \"is_key\": 1, \"row_id\": 2179919, \"text\": \"Total\"}, {\"quad\": {\"x2\": 647, \"y3\": 1153, \"x3\": 649, \"y4\": 1161, \"x1\": 418, \"y1\": 1117, \"x4\": 420, \"y2\": 1108}, \"is_key\": 0, \"row_id\": 2179919, \"text\": \"1,591,600\"}], \"category\": \"total.total_price\", \"group_id\": 26, \"sub_group_id\": 0}], \"roi\": {}, \"repeating_symbol\": [], \"dontcare\": []}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# let's load the corresponding JSON dictionary (as string representation)\n",
+    "ground_truth = example['ground_truth']\n",
+    "print(ground_truth)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "`low_cpu_mem_usage` was None, now set to True since model is quantized.\n",
+      "Loading checkpoint shards: 100%|██████████| 7/7 [00:24<00:00,  3.45s/it]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from peft import LoraConfig\n",
+    "from transformers import BitsAndBytesConfig, Idefics2ForConditionalGeneration\n",
+    "import torch\n",
+    "\n",
+    "lora_config = LoraConfig(\n",
+    "        r=8,\n",
+    "        lora_alpha=8,\n",
+    "        lora_dropout=0.1,\n",
+    "        target_modules='.*(text_model|modality_projection|perceiver_resampler).*(down_proj|gate_proj|up_proj|k_proj|q_proj|v_proj|o_proj).*$',\n",
+    "        use_dora=False,\n",
+    "        init_lora_weights=\"gaussian\"\n",
+    "    )\n",
+    "bnb_config = BitsAndBytesConfig(\n",
+    "            load_in_4bit=True,\n",
+    "            bnb_4bit_quant_type=\"nf4\",\n",
+    "            bnb_4bit_compute_dtype=torch.float16\n",
+    ")\n",
+    "\n",
+    "model = Idefics2ForConditionalGeneration.from_pretrained(\n",
+    "        \"HuggingFaceM4/idefics2-8b\",\n",
+    "        torch_dtype=torch.float16,\n",
+    "        quantization_config=bnb_config,\n",
+    "    )\n",
+    "model.add_adapter(lora_config)\n",
+    "model.enable_adapters()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create PyTorch dataset\n",
+    "\n",
+    "Here we create a regular PyTorch dataset.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-04-30 12:39:37.461173: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "2024-04-30 12:39:38.252248: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
+      "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "import random\n",
+    "from typing import Any, List, Dict\n",
+    "\n",
+    "import torch\n",
+    "from torch.utils.data import Dataset\n",
+    "\n",
+    "from transformers import AutoProcessor\n",
+    "\n",
+    "processor = AutoProcessor.from_pretrained(\"HuggingFaceM4/idefics2-8b\", do_image_splitting=False)\n",
+    "\n",
+    "added_tokens = []\n",
+    "\n",
+    "\n",
+    "class Idefics2Dataset(Dataset):\n",
+    "    \"\"\"\n",
+    "    PyTorch Dataset for Idefics2. This class takes a HuggingFace Dataset as input.\n",
+    "    \n",
+    "    Each row, consists of image path(png/jpg/jpeg) and gt data (json/jsonl/txt).\n",
+    "    \"\"\"\n",
+    "\n",
+    "    def __init__(\n",
+    "        self,\n",
+    "        dataset_name_or_path: str,\n",
+    "        split: str = \"train\",\n",
+    "        sort_json_key: bool = True,\n",
+    "    ):\n",
+    "        super().__init__()\n",
+    "\n",
+    "        self.split = split\n",
+    "        self.sort_json_key = sort_json_key\n",
+    "\n",
+    "        self.dataset = load_dataset(dataset_name_or_path, split=self.split)\n",
+    "        self.dataset_length = len(self.dataset)\n",
+    "\n",
+    "        self.gt_token_sequences = []\n",
+    "        for sample in self.dataset:\n",
+    "            ground_truth = json.loads(sample[\"ground_truth\"])\n",
+    "            if \"gt_parses\" in ground_truth:  # when multiple ground truths are available, e.g., docvqa\n",
+    "                assert isinstance(ground_truth[\"gt_parses\"], list)\n",
+    "                gt_jsons = ground_truth[\"gt_parses\"]\n",
+    "            else:\n",
+    "                assert \"gt_parse\" in ground_truth and isinstance(ground_truth[\"gt_parse\"], dict)\n",
+    "                gt_jsons = [ground_truth[\"gt_parse\"]]\n",
+    "\n",
+    "            self.gt_token_sequences.append(\n",
+    "                [\n",
+    "                    self.json2token(\n",
+    "                        gt_json,\n",
+    "                        update_special_tokens_for_json_key=self.split == \"train\",\n",
+    "                        sort_json_key=self.sort_json_key,\n",
+    "                    )\n",
+    "                    for gt_json in gt_jsons  # load json from list of json\n",
+    "                ]\n",
+    "            )\n",
+    "\n",
+    "    def json2token(self, obj: Any, update_special_tokens_for_json_key: bool = True, sort_json_key: bool = True):\n",
+    "        \"\"\"\n",
+    "        Convert an ordered JSON object into a token sequence\n",
+    "        \"\"\"\n",
+    "        if type(obj) == dict:\n",
+    "            if len(obj) == 1 and \"text_sequence\" in obj:\n",
+    "                return obj[\"text_sequence\"]\n",
+    "            else:\n",
+    "                output = \"\"\n",
+    "                if sort_json_key:\n",
+    "                    keys = sorted(obj.keys(), reverse=True)\n",
+    "                else:\n",
+    "                    keys = obj.keys()\n",
+    "                for k in keys:\n",
+    "                    if update_special_tokens_for_json_key:\n",
+    "                        self.add_tokens([fr\"<s_{k}>\", fr\"</s_{k}>\"])\n",
+    "                    output += (\n",
+    "                        fr\"<s_{k}>\"\n",
+    "                        + self.json2token(obj[k], update_special_tokens_for_json_key, sort_json_key)\n",
+    "                        + fr\"</s_{k}>\"\n",
+    "                    )\n",
+    "                return output\n",
+    "        elif type(obj) == list:\n",
+    "            return r\"<sep/>\".join(\n",
+    "                [self.json2token(item, update_special_tokens_for_json_key, sort_json_key) for item in obj]\n",
+    "            )\n",
+    "        else:\n",
+    "            obj = str(obj)\n",
+    "            if f\"<{obj}/>\" in added_tokens:\n",
+    "                obj = f\"<{obj}/>\"  # for categorical special tokens\n",
+    "            return obj\n",
+    "    \n",
+    "    def add_tokens(self, list_of_tokens: List[str]):\n",
+    "        \"\"\"\n",
+    "        Add special tokens to tokenizer and resize the token embeddings of the decoder\n",
+    "        \"\"\"\n",
+    "        newly_added_num = processor.tokenizer.add_tokens(list_of_tokens)\n",
+    "        if newly_added_num > 0:\n",
+    "            model.resize_token_embeddings(len(processor.tokenizer))\n",
+    "            added_tokens.extend(list_of_tokens)\n",
+    "    \n",
+    "    def __len__(self) -> int:\n",
+    "        return self.dataset_length\n",
+    "\n",
+    "    def __getitem__(self, idx: int) -> Dict:\n",
+    "        \"\"\"\n",
+    "        Load image from image_path of given dataset_path and convert into input_tensor and labels\n",
+    "        Convert gt data into input_ids (tokenized string)\n",
+    "        Returns:\n",
+    "            input_tensor : preprocessed image\n",
+    "            input_ids : tokenized gt_data\n",
+    "            labels : masked labels (model doesn't need to predict prompt and pad token)\n",
+    "        \"\"\"\n",
+    "        sample = self.dataset[idx]\n",
+    "\n",
+    "        # inputs\n",
+    "        image = sample[\"image\"]\n",
+    "        target_sequence = random.choice(self.gt_token_sequences[idx])  # can be more than one, e.g., DocVQA Task 1\n",
+    "        \n",
+    "        return image, target_sequence"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "train_dataset = Idefics2Dataset(\"naver-clova-ix/cord-v2\",  split=\"train\", sort_json_key=False)\n",
+    "val_dataset = Idefics2Dataset(\"naver-clova-ix/cord-v2\", split=\"validation\", sort_json_key=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can verify that a token like `</s_unitprice>` was added to the vocabulary of the tokenizer (and the model):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "''"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "processor.decode([57560])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As always, it's very important to verify whether our data is prepared correctly. Let's check the first training example:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<PIL.PngImagePlugin.PngImageFile image mode=RGB size=864x1296>,\n",
+       " '<s_menu><s_nm>Nasi Campur Bali</s_nm><s_cnt>1 x</s_cnt><s_price>75,000</s_price><sep/><s_nm>Bbk Bengil Nasi</s_nm><s_cnt>1 x</s_cnt><s_price>125,000</s_price><sep/><s_nm>MilkShake Starwb</s_nm><s_cnt>1 x</s_cnt><s_price>37,000</s_price><sep/><s_nm>Ice Lemon Tea</s_nm><s_cnt>1 x</s_cnt><s_price>24,000</s_price><sep/><s_nm>Nasi Ayam Dewata</s_nm><s_cnt>1 x</s_cnt><s_price>70,000</s_price><sep/><s_nm>Free Ice Tea</s_nm><s_cnt>3 x</s_cnt><s_price>0</s_price><sep/><s_nm>Organic Green Sa</s_nm><s_cnt>1 x</s_cnt><s_price>65,000</s_price><sep/><s_nm>Ice Tea</s_nm><s_cnt>1 x</s_cnt><s_price>18,000</s_price><sep/><s_nm>Ice Orange</s_nm><s_cnt>1 x</s_cnt><s_price>29,000</s_price><sep/><s_nm>Ayam Suir Bali</s_nm><s_cnt>1 x</s_cnt><s_price>85,000</s_price><sep/><s_nm>Tahu Goreng</s_nm><s_cnt>2 x</s_cnt><s_price>36,000</s_price><sep/><s_nm>Tempe Goreng</s_nm><s_cnt>2 x</s_cnt><s_price>36,000</s_price><sep/><s_nm>Tahu Telor Asin</s_nm><s_cnt>1 x</s_cnt><s_price>40,000.</s_price><sep/><s_nm>Nasi Goreng Samb</s_nm><s_cnt>1 x</s_cnt><s_price>70,000</s_price><sep/><s_nm>Bbk Panggang Sam</s_nm><s_cnt>3 x</s_cnt><s_price>366,000</s_price><sep/><s_nm>Ayam Sambal Hija</s_nm><s_cnt>1 x</s_cnt><s_price>92,000</s_price><sep/><s_nm>Hot Tea</s_nm><s_cnt>2 x</s_cnt><s_price>44,000</s_price><sep/><s_nm>Ice Kopi</s_nm><s_cnt>1 x</s_cnt><s_price>32,000</s_price><sep/><s_nm>Tahu Telor Asin</s_nm><s_cnt>1 x</s_cnt><s_price>40,000</s_price><sep/><s_nm>Free Ice Tea</s_nm><s_cnt>1 x</s_cnt><s_price>0</s_price><sep/><s_nm>Bebek Street</s_nm><s_cnt>1 x</s_cnt><s_price>44,000</s_price><sep/><s_nm>Ice Tea Tawar</s_nm><s_cnt>1 x</s_cnt><s_price>18,000</s_price></s_menu><s_sub_total><s_subtotal_price>1,346,000</s_subtotal_price><s_service_price>100,950</s_service_price><s_tax_price>144,695</s_tax_price><s_etc>-45</s_etc></s_sub_total><s_total><s_total_price>1,591,600</s_total_price></s_total>')"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_dataset[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Create PyTorch DataLoaders\n",
+    "\n",
+    "Next, we create corresponding PyTorch DataLoaders, which allow us to loop over the dataset in batches:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from torch.utils.data import DataLoader\n",
+    "\n",
+    "image_token_id = processor.tokenizer.additional_special_tokens_ids[processor.tokenizer.additional_special_tokens.index(\"<image>\")]\n",
+    "\n",
+    "\n",
+    "def collate_fn(examples):\n",
+    "    texts = []\n",
+    "    images = []\n",
+    "    answers = []\n",
+    "    for example in examples:\n",
+    "        image, ground_truth = example\n",
+    "        messages = [\n",
+    "            {\n",
+    "                \"role\": \"user\",\n",
+    "                \"content\": [\n",
+    "                    {\"type\": \"text\", \"text\": \"Extract JSON.\"},\n",
+    "                    {\"type\": \"image\"},\n",
+    "                ]\n",
+    "            },\n",
+    "            {\n",
+    "                \"role\": \"assistant\",\n",
+    "                \"content\": [\n",
+    "                    {\"type\": \"text\", \"text\": ground_truth}\n",
+    "                ]\n",
+    "            }\n",
+    "        ]\n",
+    "        text = processor.apply_chat_template(messages, add_generation_prompt=False)\n",
+    "        texts.append(text.strip())\n",
+    "        images.append([image])\n",
+    "        answers.append(ground_truth)\n",
+    "\n",
+    "    batch = processor(text=texts, images=images, return_tensors=\"pt\", padding=True)\n",
+    "\n",
+    "    labels = batch[\"input_ids\"].clone()\n",
+    "    labels[labels == processor.tokenizer.pad_token_id] = image_token_id\n",
+    "    batch[\"labels\"] = labels\n",
+    "\n",
+    "    batch[\"images\"] = images\n",
+    "    batch[\"answers\"] = answers\n",
+    "\n",
+    "    input_ids = batch[\"input_ids\"]\n",
+    "    attention_mask = batch[\"attention_mask\"]\n",
+    "    pixel_values = batch[\"pixel_values\"]\n",
+    "    pixel_attention_mask = batch[\"pixel_attention_mask\"]\n",
+    "    labels = batch[\"labels\"]\n",
+    "    \n",
+    "    return input_ids, attention_mask, pixel_values, pixel_attention_mask, labels, images, answers\n",
+    "\n",
+    "# feel free to increase the batch size if you have a lot of memory\n",
+    "# I'm fine-tuning on Colab and given the large image size, batch size > 1 is not feasible\n",
+    "train_dataloader = DataLoader(train_dataset, collate_fn=collate_fn, batch_size=2, shuffle=True, num_workers=4)\n",
+    "val_dataloader = DataLoader(val_dataset, collate_fn=collate_fn, batch_size=2, shuffle=False, num_workers=4)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Let's verify a batch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n"
+     ]
+    }
+   ],
+   "source": [
+    "input_ids, attention_mask, pixel_values, pixel_attention_mask, labels, images, answers = next(iter(train_dataloader))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['<unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><unk><s> User: Extract JSON.<fake_token_around_image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><fake_token_around_image><end_of_utterance> \\nAssistant:<s_menu><s_nm>MILK PASTRY ROLL</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>CARAMEL PASTRY</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price></s_menu><s_total><s_total_price>21,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>29,000</s_changeprice></s_total><end_of_utterance>', '<s> User: Extract JSON.<fake_token_around_image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><image><fake_token_around_image><end_of_utterance> \\nAssistant:<s_menu><s_nm>Viet Milk Coffee</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price><s_sub><s_nm>+Hot</s_nm><sep/><s_nm>+M</s_nm></s_sub></s_menu><s_sub_total><s_subtotal_price>25.000</s_subtotal_price></s_sub_total><s_total><s_total_price>25.000</s_total_price><s_cashprice>30.000</s_cashprice><s_changeprice>5.000</s_changeprice></s_total><end_of_utterance>']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(processor.batch_decode(input_ids))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Define LightningModule\n",
+    "\n",
+    "Next, we define a [LightningModule](https://pytorch-lightning.readthedocs.io/en/stable/common/lightning_module.html), which is the standard way to train a model in PyTorch Lightning. A LightningModule is an `nn.Module` with some additional functionality. \n",
+    "\n",
+    "Basically, PyTorch Lightning will take care of all device placements (`.to(device)`) for us, as well as the backward pass, putting the model in training mode, etc."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import re\n",
+    "from nltk import edit_distance\n",
+    "import numpy as np\n",
+    "\n",
+    "import lightning as L\n",
+    "\n",
+    "\n",
+    "class Idefics2ModelPLModule(L.LightningModule):\n",
+    "    def __init__(self, config, processor, model):\n",
+    "        super().__init__()\n",
+    "        self.config = config\n",
+    "        self.processor = processor\n",
+    "        self.model = model\n",
+    "\n",
+    "    def training_step(self, batch, batch_idx):\n",
+    "\n",
+    "        input_ids, attention_mask, pixel_values, pixel_attention_mask, labels, images, answers = batch\n",
+    "\n",
+    "        outputs = self.model(input_ids=input_ids,\n",
+    "                                attention_mask=attention_mask,\n",
+    "                                pixel_values=pixel_values,\n",
+    "                                pixel_attention_mask=pixel_attention_mask,\n",
+    "                                labels=labels)\n",
+    "        loss = outputs.loss\n",
+    "        \n",
+    "        self.log(\"train_loss\", loss)\n",
+    "        \n",
+    "        return loss\n",
+    "\n",
+    "    def validation_step(self, batch, batch_idx, dataset_idx=0):\n",
+    "        \n",
+    "        input_ids, attention_mask, pixel_values, pixel_attention_mask, labels, images, answers = batch\n",
+    "        texts = []\n",
+    "        \n",
+    "        # we feed the prompt to the model\n",
+    "        for _ in range(len(answers)):\n",
+    "            messages = [\n",
+    "                {\n",
+    "                    \"role\": \"user\",\n",
+    "                    \"content\": [\n",
+    "                        {\"type\": \"text\", \"text\": \"Extract JSON.\"},\n",
+    "                        {\"type\": \"image\"},\n",
+    "                    ]\n",
+    "                }\n",
+    "            ]\n",
+    "            text = processor.apply_chat_template(messages, add_generation_prompt=True)\n",
+    "            texts.append(text.strip())\n",
+    "        inputs = processor(text=texts, images=images, padding=True, return_tensors=\"pt\")\n",
+    "        generated_ids = model.generate(**inputs, max_new_tokens=64)\n",
+    "        generated_texts = processor.batch_decode(generated_ids[:, inputs[\"input_ids\"].size(1):], skip_special_tokens=True)\n",
+    "    \n",
+    "        predictions = []\n",
+    "        for seq in generated_texts:\n",
+    "            seq = seq.replace(self.processor.tokenizer.eos_token, \"\").replace(self.processor.tokenizer.pad_token, \"\")\n",
+    "            seq = re.sub(r\"<.*?>\", \"\", seq, count=1).strip()  # remove first task start token\n",
+    "            predictions.append(seq)\n",
+    "\n",
+    "        scores = []\n",
+    "        for pred, answer in zip(predictions, answers):\n",
+    "            pred = re.sub(r\"(?:(?<=>) | (?=</s_))\", \"\", pred)\n",
+    "            answer = answer.replace(self.processor.tokenizer.eos_token, \"\") \n",
+    "\n",
+    "            scores.append(edit_distance(pred, answer) / max(len(pred), len(answer)))\n",
+    "\n",
+    "            if self.config.get(\"verbose\", False) and len(scores) == 1:\n",
+    "                print(f\"Prediction: {pred}\")\n",
+    "                print(f\"    Answer: {answer}\")\n",
+    "                print(f\" Normed ED: {scores[0]}\")\n",
+    "\n",
+    "        self.log(\"val_edit_distance\", np.mean(scores))\n",
+    "        \n",
+    "        return scores\n",
+    "\n",
+    "    def configure_optimizers(self):\n",
+    "        # you could also add a learning rate scheduler if you want\n",
+    "        optimizer = torch.optim.AdamW(self.parameters(), lr=self.config.get(\"lr\"))\n",
+    "    \n",
+    "        return optimizer\n",
+    "\n",
+    "    def train_dataloader(self):\n",
+    "        return train_dataloader\n",
+    "\n",
+    "    def val_dataloader(self):\n",
+    "        return val_dataloader"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Train\n",
+    "\n",
+    "Next, let's train! This happens instantiating a PyTorch Lightning `Trainer`, and then calling `trainer.fit`.\n",
+    "\n",
+    "What's great is that we can automatically train on the hardware we have (in our case, a single GPU), enable mixed precision (`fp16=True`, which makes sure we don't consume as much memory), add Weights and Biases logging, and so on. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "config = {\"max_epochs\": 10,\n",
+    "          \"val_check_interval\": 0.2, # how many times we want to validate during an epoch\n",
+    "          \"check_val_every_n_epoch\": 1,\n",
+    "          \"gradient_clip_val\": 1.0,\n",
+    "          \"num_training_samples_per_epoch\": 800,\n",
+    "          \"lr\": 1e-4,\n",
+    "          \"train_batch_sizes\": [8],\n",
+    "          \"val_batch_sizes\": [2],\n",
+    "          # \"seed\":2022,\n",
+    "          \"num_nodes\": 1,\n",
+    "          \"warmup_steps\": 50,\n",
+    "          \"result_path\": \"./result\",\n",
+    "          \"verbose\": True,\n",
+    "          }\n",
+    "\n",
+    "model_module = Idefics2ModelPLModule(config, processor, model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's start training!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/niels/python_projects/transformers/env/lib/python3.8/site-packages/lightning/fabric/connector.py:563: `precision=16` is supported for historical reasons but its usage is discouraged. Please set your precision to 16-mixed instead!\n",
+      "Using 16bit Automatic Mixed Precision (AMP)\n",
+      "GPU available: True (cuda), used: True\n",
+      "TPU available: False, using: 0 TPU cores\n",
+      "IPU available: False, using: 0 IPUs\n",
+      "HPU available: False, using: 0 HPUs\n",
+      "You are using a CUDA device ('NVIDIA A100-SXM4-80GB') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision\n",
+      "Failed to detect the name of this notebook, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable to enable code saving.\n",
+      "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mnielsrogge\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "Tracking run with wandb version 0.16.6"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Run data is saved locally in <code>./wandb/run-20240430_124040-t3hdwi09</code>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "Syncing run <strong><a href='https://wandb.ai/nielsrogge/Idefics2/runs/t3hdwi09' target=\"_blank\">demo-run-cord</a></strong> to <a href='https://wandb.ai/nielsrogge/Idefics2' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       " View project at <a href='https://wandb.ai/nielsrogge/Idefics2' target=\"_blank\">https://wandb.ai/nielsrogge/Idefics2</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       " View run at <a href='https://wandb.ai/nielsrogge/Idefics2/runs/t3hdwi09' target=\"_blank\">https://wandb.ai/nielsrogge/Idefics2/runs/t3hdwi09</a>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2,3,4]\n",
+      "\n",
+      "  | Name  | Type                             | Params\n",
+      "-----------------------------------------------------------\n",
+      "0 | model | Idefics2ForConditionalGeneration | 4.4 B \n",
+      "-----------------------------------------------------------\n",
+      "23.3 M    Trainable params\n",
+      "4.3 B     Non-trainable params\n",
+      "4.4 B     Total params\n",
+      "17,439.532Total estimated model params size (MB)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 0:   0%|          | 0/400 [00:00<?, ?it/s] "
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 0:  20%|██        | 80/400 [01:02<04:10,  1.28it/s, v_num=wi09]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": []
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "No chat template is set for this tokenizer, falling back to a default class-level template. This is very error-prone, because models are often trained with templates different from the class default! Default chat templates are a legacy feature and will be removed in Transformers v4.43, at which point any code depending on them will stop working. We recommend setting a valid chat template before then to ensure that this model continues working without issues.\n",
+      "/home/niels/python_projects/transformers/src/transformers/generation/utils.py:1542: UserWarning: You are calling .generate() with the `input_ids` being on a device type different than your model's device. `input_ids` is on cpu, whereas the model is on cuda. You may experience unexpected behaviors or slower generation. Please make sure that you have put `input_ids` to the correct device by calling for example input_ids = input_ids.to('cuda') before running `.generate()`.\n",
+      "  warnings.warn(\n",
+      "The `seen_tokens` attribute is deprecated and will be removed in v4.41. Use the `cache_position` model input instead.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Prediction: <s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s\n",
+      "    Answer: <s_menu><s_nm>REAL GANACHE</s_nm><s_cnt>1</s_cnt><s_price>16,500</s_price><sep/><s_nm>EGG TART</s_nm><s_cnt>1</s_cnt><s_price>13,000</s_price><sep/><s_nm>PIZZA TOAST</s_nm><s_cnt>1</s_cnt><s_price>16,000</s_price></s_menu><s_total><s_total_price>45,500</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>4,500</s_changeprice></s_total>\n",
+      " Normed ED: 0.7002881844380403\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/niels/python_projects/transformers/env/lib/python3.8/site-packages/lightning/pytorch/utilities/data.py:77: Trying to infer the `batch_size` from an ambiguous collection. The batch size we found is 2. To avoid any miscalculations, use `self.log(..., batch_size=batch_size)`.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Prediction: <s_nm>S-Ovaltine</s_nm><s_cnt>1</s_cnt><s_price>20,000,000</s_price><s_sub><s_nm>PB1</s_nm><s_price\n",
+      "    Answer: <s_menu><s_nm>S-Ovaltine 50%</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price><s_vatyn>10% Tax Included</s_vatyn></s_menu><s_sub_total><s_subtotal_price>18,181</s_subtotal_price><s_tax_price>1,818</s_tax_price></s_sub_total><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+      " Normed ED: 0.7617801047120419\n",
+      "Prediction: <s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><s_sub><s_nm>- Sedang</s_nm><s_cnt>1</s_\n",
+      "    Answer: <s_menu><s_nm>BBQ Chicken</s_nm><s_cnt>1</s_cnt><s_price>41,000</s_price><s_sub><s_nm>Sedang</s_nm><s_cnt>1</s_cnt><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>41,000</s_subtotal_price></s_sub_total><s_total><s_total_price>41,000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>:9,000</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+      " Normed ED: 0.7342105263157894\n",
+      "Prediction: <s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>OREO GREEN TEA SP<s_nm>AD</s\n",
+      "    Answer: <s_menu><s_nm>POTATO SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>OREO GREEN TEA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price><sep/><s_nm>WHITE CHOCO BANANA SPREAD</s_nm><s_cnt>1</s_cnt><s_price>52,000</s_price></s_menu><s_total><s_total_price>123,000</s_total_price><s_creditcardprice>123,000</s_creditcardprice></s_total>\n",
+      " Normed ED: 0.6833333333333333\n",
+      "Prediction: <s_nm>TALAM UNGU</s_nm><s_cnt>3</s_cnt><s_price>19,500</s_price><s_sub><s_nm>-40,000%</s_nm><s\n",
+      "    Answer: <s_menu><s_nm>TALAM UNGU</s_nm><s_unitprice>@6500</s_unitprice><s_cnt>3X</s_cnt><s_discountprice>-7,800</s_discountprice><s_price>19,500</s_price><sep/><s_nm>MIKA KECIL</s_nm><s_unitprice>@0</s_unitprice><s_cnt>1X</s_cnt><s_price>0</s_price></s_menu><s_sub_total><s_subtotal_price>11,700</s_subtotal_price></s_sub_total><s_total><s_total_price>11,700</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>8,300</s_changeprice><s_menuqty_cnt>4.00xITEMs</s_menuqty_cnt></s_total>\n",
+      " Normed ED: 0.8148148148148148\n",
+      "Prediction: <s_nm>Serbu 1</s_nm><s_cnt>2</s_cnt><s_price>40,000</s_price><sep/><s_nm>Choco Peanut Bread</s_nm><s_cnt>2\n",
+      "    Answer: <s_menu><s_nm>Serbu 1</s_nm><s_cnt>2</s_cnt><s_price>40.000</s_price><sep/><s_nm>Choco Peanut Bread</s_nm><s_cnt>2</s_cnt><s_price>20.000</s_price></s_menu><s_total><s_total_price>60.000</s_total_price><s_cashprice>60.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+      " Normed ED: 0.6209386281588448\n",
+      "Prediction: <s_nm>ES KOPI SUSU</s_nm><s_cnt>4</s_cnt><s_price>72.000</s_price></s_menu><s_sub_total><s_subtotal_price>72.0\n",
+      "    Answer: <s_menu><s_nm>ES KOPI SUSU</s_nm><s_cnt>4</s_cnt><s_price>72.000</s_price></s_menu><s_total><s_total_price>72.000</s_total_price><s_changeprice>0</s_changeprice><s_emoneyprice>72.000</s_emoneyprice></s_total>\n",
+      " Normed ED: 0.5144230769230769\n",
+      "Prediction: <s_nm>Arem Arem</s_nm><s_unitprice>@12.000</s_unitprice><s_cnt>2x</s_cnt><s_price>24.000</s_price><s_sub><s_\n",
+      "    Answer: <s_menu><s_nm>Arem Arem</s_nm><s_unitprice>@ 12.000</s_unitprice><s_cnt>2 x</s_cnt><s_price>24.000</s_price><sep/><s_nm>Kroket</s_nm><s_unitprice>@ 12.000</s_unitprice><s_cnt>1 x</s_cnt><s_price>12.000</s_price></s_menu><s_sub_total><s_subtotal_price>Rp 36.000</s_subtotal_price><s_tax_price>Rp 3.600</s_tax_price></s_sub_total><s_total><s_total_price>Rp 39.600</s_total_price><s_emoneyprice>Rp 39.600</s_emoneyprice></s_total>\n",
+      " Normed ED: 0.747072599531616\n",
+      "Prediction: <s_nm>TOTAL CASH CHANGE</s_nm><s_unitprice>20,000,000</s_unitprice><s_cnt>32</s_cnt><s_price>20,000,00\n",
+      "    Answer: <s_menu><s_nm>TT</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+      " Normed ED: 0.703862660944206\n",
+      "Prediction: <s_nm>BEEF C ROLL 3PCS</s_nm><s_cnt>1</s_cnt><s_price>10,000</s_price><sep/><s_nm>KAYA BRED</s_nm><\n",
+      "    Answer: <s_menu><s_nm>beef C roll 3pcs</s_nm><s_unitprice>10,000</s_unitprice><s_cnt>1</s_cnt><s_price>10,000</s_price><sep/><s_nm>kaya bred</s_nm><s_unitprice>15,000</s_unitprice><s_cnt>1</s_cnt><s_price>15,000</s_price></s_menu><s_total><s_total_price>25,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>75,000</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+      " Normed ED: 0.7900262467191601\n",
+      "Prediction: <s_nm>JAMUR</s_nm><s_cnt>2</s_cnt><s_price>10,000</s_price><sep/><s_nm>TAHU</s_nm><s_cnt>1</s_cnt><\n",
+      "    Answer: <s_menu><s_nm>JAMUR</s_nm><s_cnt>2</s_cnt><s_price>10,000</s_price><sep/><s_nm>TAHU</s_nm><s_cnt>1</s_cnt><s_price>5,000</s_price></s_menu><s_sub_total><s_subtotal_price>15,000</s_subtotal_price><s_tax_price>1,500</s_tax_price></s_sub_total><s_total><s_total_price>16,500</s_total_price><s_cashprice>20,000</s_cashprice><s_changeprice>3,500</s_changeprice></s_total>\n",
+      " Normed ED: 0.7295081967213115\n",
+      "Prediction: <s_nm>RedVelvet Nutella</s_nm><s_cnt>1</s_cnt><s_price>280,000</s_price><sep/><s_nm>5 Free Mini Candle</s_nm><s_cnt>5\n",
+      "    Answer: <s_menu><s_nm>RedVelvet Nutella</s_nm><s_cnt>1</s_cnt><s_price>280,000</s_price><s_sub><s_nm>Free Mini Candle</s_nm><s_cnt>.5</s_cnt><sep/><s_nm>Large Box</s_nm><s_cnt>1</s_cnt></s_sub></s_menu><s_sub_total><s_subtotal_price>280,000</s_subtotal_price><s_tax_price>28,000</s_tax_price></s_sub_total><s_total><s_total_price>308,000</s_total_price><s_creditcardprice>308,000</s_creditcardprice></s_total>\n",
+      " Normed ED: 0.7256857855361596\n",
+      "Prediction: <s_nm>PAIN AU CHOCOLATE</s_nm><s_cnt>1</s_cnt><s_price>11,000</s_price><sep/><s_nm>CHOCO CUSTARD PASTRY</s_nm><\n",
+      "    Answer: <s_menu><s_nm>PAIN AU CHOCOLATE</s_nm><s_cnt>1</s_cnt><s_price>11,000</s_price><sep/><s_nm>CHOCO CUSTARD PASTRY</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>MILK PASTRY ROLL</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>REAL CHEESE INSIDE BREAD</s_nm><s_cnt>1</s_cnt><s_price>13,500</s_price><sep/><s_nm>SAUSAGE BREAD</s_nm><s_cnt>1</s_cnt><s_price>15,000</s_price><sep/><s_nm>HAM CHEESE FLAT BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>80,500</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>19,500</s_changeprice></s_total>\n",
+      " Normed ED: 0.8174342105263158\n",
+      "Prediction: <s_nm>NASI MERAH/PUTIH</s_nm><s_unitprice>5,000</s_unitprice><s_cnt>1x</s_cnt><s_price>5,000</s_price><sep\n",
+      "    Answer: <s_menu><s_nm>NASI MERAH/PUTIH</s_nm><s_unitprice>5.000</s_unitprice><s_cnt>1x</s_cnt><s_price>5.000</s_price><sep/><s_nm>SAYUR</s_nm><s_unitprice>4.000</s_unitprice><s_cnt>2x</s_cnt><s_price>8.000</s_price><sep/><s_nm>KERUPUK/SAMBEL</s_nm><s_unitprice>2.000</s_unitprice><s_cnt>1x</s_cnt><s_price>2.000</s_price><sep/><s_nm>AYAM</s_nm><s_unitprice>14.000</s_unitprice><s_cnt>1x</s_cnt><s_price>14.000</s_price><sep/><s_nm>MINUMAN KEMASAN/REFILL</s_nm><s_unitprice>6.000</s_unitprice><s_cnt>1x</s_cnt><s_price>6.000</s_price></s_menu><s_total><s_total_price>Rp. 35.000</s_total_price></s_total>\n",
+      " Normed ED: 0.8249158249158249\n",
+      "Prediction: <s_nm>ELEPHANT READ BEAN</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>CHAPSAL TWISTER DONUT</s_nm\n",
+      "    Answer: <s_menu><s_nm>ELEPHANT READ BEAN</s_nm><s_unitprice>12,000</s_unitprice><s_cnt>1</s_cnt><s_price>12,000</s_price><sep/><s_nm>chapsal twister donnut</s_nm><s_unitprice>10,000</s_unitprice><s_cnt>1</s_cnt><s_price>10,000</s_price></s_menu><s_total><s_total_price>22,000</s_total_price><s_cashprice>22,000</s_cashprice><s_changeprice>0</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+      " Normed ED: 0.764102564102564\n",
+      "Prediction: <s_nm>REDBEAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>FRANKFUT S/USAGE ROLL</s_nm\n",
+      "    Answer: <s_menu><s_nm>REDBEAN BRE/D</s_nm><s_cnt>1</s_cnt><s_price>9,000</s_price><sep/><s_nm>FRANKFRUT S/USAGE ROLL</s_nm><s_cnt>1</s_cnt><s_price>12,000</s_price></s_menu><s_total><s_total_price>21,000</s_total_price><s_cashprice>50,000</s_cashprice><s_changeprice>29,000</s_changeprice></s_total>\n",
+      " Normed ED: 0.6426116838487973\n",
+      "Prediction: <s_nm>Nasi (MLY)</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price></s_menu><s_sub_total><s_subtotal_price>6.000</s\n",
+      "    Answer: <s_menu><s_nm>Nasi (MLY)</s_nm><s_cnt>1</s_cnt><s_price>6.000</s_price></s_menu><s_sub_total><s_subtotal_price>6.000</s_subtotal_price></s_sub_total><s_total><s_total_price>6.000</s_total_price><s_emoneyprice>6.000</s_emoneyprice></s_total>\n",
+      " Normed ED: 0.5375\n",
+      "Prediction: <s_nm>GRILLED BABY POTATO ( R</s_nm><s_cnt>1</s_cnt><s_price>50,500</s_price><sep/><s_nm>TRUFFLE CREAM</s_\n",
+      "    Answer: <s_menu><s_nm>GRILLED BABY POTATO (R</s_nm><s_cnt>1</s_cnt><s_price>50,500</s_price><sep/><s_nm>TRUFFLE CREAM</s_nm><s_cnt>1</s_cnt><s_price>76,000</s_price><sep/><s_nm>CARBONARA</s_nm><s_cnt>1</s_cnt><s_price>70,500</s_price><sep/><s_nm>ORIGINAL BREWED TEA</s_nm><s_cnt>2</s_cnt><s_price>46,000</s_price></s_menu><s_sub_total><s_subtotal_price>243,000</s_subtotal_price><s_service_price>14,580</s_service_price><s_tax_price>25,758</s_tax_price></s_sub_total><s_total><s_total_price>283,338</s_total_price><s_creditcardprice>283,338<sep/>5962</s_creditcardprice></s_total>\n",
+      " Normed ED: 0.8181818181818182\n",
+      "Prediction: <s_nm>Soft Gri 3 Tap</s_nm><s_cnt>1</s_cnt><s_price>17,272</s_price><sep/><s_nm>Top Dro</s_creditcardprice></s_nm><s_cnt>1\n",
+      "    Answer: <s_menu><s_nm>Soft Ori 3 Top</s_nm><s_cnt>1</s_cnt><s_price>17,272</s_price><s_sub><s_nm>Top Oreo</s_nm><s_price>0</s_price><sep/><s_nm>Top Oreo</s_nm><s_price>0</s_price><sep/><s_nm>Top Banana</s_nm><s_price>0</s_price></s_sub></s_menu><s_sub_total><s_subtotal_price>17,272</s_subtotal_price><s_tax_price>1,727</s_tax_price></s_sub_total><s_total><s_total_price>18,999</s_total_price><s_cashprice>18,999</s_cashprice></s_total>\n",
+      " Normed ED: 0.7336448598130841\n",
+      "Prediction: <s_nm>TOTAL CASH CHANGE</s_nm><s_unitprice>20,000,000</s_unitprice><s_cnt>33</s_cnt><s_price>20,000,00\n",
+      "    Answer: <s_menu><s_nm>TT</s_nm><s_unitprice>20,000</s_unitprice><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+      " Normed ED: 0.703862660944206\n",
+      "Prediction: <s_nm>Gojek Chicken</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>Chili Sauce H</s_nm><s_cnt>1</s\n",
+      "    Answer: <s_menu><s_nm>Gojek Chicken Chilli Sauce H</s_nm><s_cnt>1</s_cnt><s_price>95,000</s_price><sep/><s_nm>Gojek Chicken Soy Sauce F</s_nm><s_cnt>1</s_cnt><s_price>180,000</s_price><sep/><s_nm>Gojek French Fries</s_nm><s_cnt>1</s_cnt><s_price>70,000</s_price></s_menu><s_sub_total><s_subtotal_price>345,000</s_subtotal_price><s_discount_price>0</s_discount_price><s_service_price>0</s_service_price><s_tax_price>34,500</s_tax_price></s_sub_total><s_total><s_total_price>379,500</s_total_price></s_total>\n",
+      " Normed ED: 0.785140562248996\n",
+      "Prediction: <s_nm>STIX CINNAMON</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>CINNAMONSUGAR</s_nm><s\n",
+      "    Answer: <s_menu><s_nm>STIX CINNAMON</s_nm><s_unitprice>19,000</s_unitprice><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>CINNAMON SUGAR</s_nm><s_unitprice>17,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_price><sep/><s_nm>TRIPPLE CHEESE</s_nm><s_unitprice>17,000</s_unitprice><s_cnt>1</s_cnt><s_price>17,000</s_price></s_menu><s_sub_total><s_subtotal_price>53,000</s_subtotal_price></s_sub_total><s_total><s_total_price>53,000</s_total_price><s_changeprice>0</s_changeprice><s_creditcardprice>53,000</s_creditcardprice></s_total>\n",
+      " Normed ED: 0.8108614232209738\n",
+      "Prediction: <s_nm>THAI ICED TEA (L)</s_nm><s_cnt>1</s_cnt><s_price>16,363</s_price></s_menu><s_sub_total><s_subtotal_price>16,\n",
+      "    Answer: <s_menu><s_nm>THAI ICED TEA (L)</s_nm><s_unitprice>16,363</s_unitprice><s_cnt>1</s_cnt><s_price>16.363</s_price></s_menu><s_sub_total><s_subtotal_price>16.363</s_subtotal_price><s_tax_price>1,636</s_tax_price></s_sub_total><s_total><s_total_price>17,999</s_total_price><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+      " Normed ED: 0.6366559485530546\n",
+      "Prediction: <s_nm>MARBLE CASTELA</s_nm><s_cnt>1</s_cnt><s_price>22,000</s_price></s_menu><s_total><s_total_price>22,000\n",
+      "    Answer: <s_menu><s_nm>MARBLE CASTELA</s_nm><s_unitprice>22,000</s_unitprice><s_cnt>1</s_cnt><s_price>22,000</s_price></s_menu><s_total><s_total_price>22,000</s_total_price><s_cashprice>22,000</s_cashprice><s_changeprice>0</s_changeprice><s_menuqty_cnt>1</s_menuqty_cnt></s_total>\n",
+      " Normed ED: 0.6051660516605166\n",
+      "Prediction: <s_nm>SB 1 OR</s_nm><s_cnt>1</s_cnt><s_price>28,636</s_price><sep/><s_nm>Chokocha Fit</s_nm><s_cnt>1</\n",
+      "    Answer: <s_menu><s_nm>SB 1 OR</s_nm><s_cnt>1</s_cnt><s_price>28,636</s_price><sep/><s_nm>Chokocha Flt</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price><sep/><s_nm>Bbq Bento</s_nm><s_cnt>1</s_cnt><s_price>13,636</s_price></s_menu><s_sub_total><s_subtotal_price>55,908</s_subtotal_price><s_tax_price>5,592</s_tax_price></s_sub_total><s_total><s_total_price>61,500</s_total_price><s_cashprice>70,000</s_cashprice><s_changeprice>8,500</s_changeprice><s_menuqty_cnt>3</s_menuqty_cnt></s_total>\n",
+      " Normed ED: 0.7866108786610879\n",
+      "Prediction: <s_nm>CHOCOLATE ECLAIR</s_nm><s_cnt>2</s_cnt><s_price>26,000</s_price></s_menu><s_total><s_total_price>26,000\n",
+      "    Answer: <s_menu><s_nm>CHOCOLATE ECLAIR</s_nm><s_cnt>2</s_cnt><s_price>26,000</s_price></s_menu><s_total><s_total_price>26,000</s_total_price><s_cashprice>26,000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+      " Normed ED: 0.47596153846153844\n",
+      "Prediction: <s_nm>KENTHIR 2</s_nm><s_cnt>2</s_cnt><s_price>42.000</s_price><sep/><s_nm>KOL GORENG</s_nm><s_cnt>2\n",
+      "    Answer: <s_menu><s_nm>KENTHIR 2</s_nm><s_cnt>2</s_cnt><s_price>42.000</s_price><sep/><s_nm>KOL GORENG</s_nm><s_cnt>2</s_cnt><s_price>6.000</s_price><sep/><s_nm>TEH MANIS</s_nm><s_cnt>2</s_cnt><s_price>8.000</s_price></s_menu><s_sub_total><s_subtotal_price>56.000</s_subtotal_price></s_sub_total><s_total><s_total_price>56.000</s_total_price><s_cashprice>56.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+      " Normed ED: 0.7549019607843137\n",
+      "Prediction: <s_nm>4003-Blueberry Fujji</s_nm><s_cnt>40.000</s_cnt><s_price>40.000</s_price><sep/><s_nm>6001-Pl\n",
+      "    Answer: <s_menu><s_nm>4003-Blueberry Fuji</s_nm><s_unitprice>40.000</s_unitprice><s_cnt>x1</s_cnt><s_price>40.000</s_price><sep/><s_nm>6001-Plastic Bag Small</s_nm><s_unitprice>0</s_unitprice><s_cnt>x1</s_cnt><s_price>0</s_price></s_menu><s_total><s_total_price>40.000</s_total_price><s_cashprice>50.000</s_cashprice><s_changeprice>10.000</s_changeprice><s_menuqty_cnt>2</s_menuqty_cnt></s_total>\n",
+      " Normed ED: 0.7551546391752577\n",
+      "Prediction: <s_nm>Thai Iced T.x1</s_nm><s_cnt>1</s_cnt><s_price>20.000</s_price></s_menu><s_sub_total><s_subtotal_price>20.\n",
+      "    Answer: <s_menu><s_nm>Thai Iced T. .x1</s_nm><s_price>20.000</s_price></s_menu><s_sub_total><s_subtotal_price>20.000</s_subtotal_price></s_sub_total><s_total><s_total_price>20.000</s_total_price><s_cashprice>20.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+      " Normed ED: 0.6412213740458015\n",
+      "Prediction: <s_nm>Viet Milk Coffee</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price><s_sub><s_nm>+M</s_nm><s_price>0</s_\n",
+      "    Answer: <s_menu><s_nm>Viet Milk Coffee</s_nm><s_cnt>1</s_cnt><s_price>25.000</s_price><s_sub><s_nm>+Hot</s_nm><sep/><s_nm>+M</s_nm></s_sub></s_menu><s_sub_total><s_subtotal_price>25.000</s_subtotal_price></s_sub_total><s_total><s_total_price>25.000</s_total_price><s_cashprice>25.000</s_cashprice><s_changeprice>0</s_changeprice></s_total>\n",
+      " Normed ED: 0.6797583081570997\n",
+      "Prediction: <s_nm>VANILLA CHOCOL HEART CAKE</s_nm><s_cnt>1</s_cnt><s_price>180,000</s_price></s_menu><s_sub_total><s_subtotal_price\n",
+      "    Answer: <s_menu><s_nm>VANILLA CHOCO HEART CAKE</s_nm><s_cnt>1</s_cnt><s_price>180,000</s_price></s_menu><s_total><s_total_price>180,000</s_total_price><s_creditcardprice>180,000</s_creditcardprice></s_total>\n",
+      " Normed ED: 0.45226130653266333\n",
+      "Prediction: <s_nm>French Fries</s_nm><s_cnt>1</s_cnt><s_price>10,909</s_price><sep/><s_nm>Cheese Burger</s_nm><s_cnt>2</s_\n",
+      "    Answer: <s_menu><s_nm>French Fries</s_nm><s_cnt>1</s_cnt><s_price>10,909</s_price><sep/><s_nm>Cheese Burger</s_nm><s_cnt>2</s_cnt><s_price>36,364</s_price><sep/><s_nm>Milo</s_nm><s_cnt>1</s_cnt><s_price>9.091</s_price></s_menu><s_sub_total><s_subtotal_price>56,364</s_subtotal_price><s_tax_price>5,636</s_tax_price></s_sub_total><s_total><s_total_price>62,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>38,000</s_changeprice></s_total>\n",
+      " Normed ED: 0.7544642857142857\n",
+      "Prediction: <s_nm>WHOLE WHEAT PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,00\n",
+      "    Answer: <s_menu><s_nm>WHOLE WHEAT PAN BREAD</s_nm><s_cnt>1</s_cnt><s_price>20,000</s_price></s_menu><s_total><s_total_price>20,000</s_total_price><s_cashprice>100,000</s_cashprice><s_changeprice>80,000</s_changeprice></s_total>\n",
+      " Normed ED: 0.4840182648401826\n",
+      "Prediction: <s_nm>AIR MINERAL</s_nm><s_unitprice>7,000</s_unitprice><s_cnt>7</s_cnt><s_price>7,000</s_price></s_menu><s_sub_\n",
+      "    Answer: <s_menu><s_nm>AIR MINERAL</s_nm><s_price>7,000</s_price></s_menu><s_total><s_total_price>7,000</s_total_price><s_cashprice>7,000</s_cashprice></s_total>\n",
+      " Normed ED: 0.47368421052631576\n",
+      "Prediction: <s_nm>Honey Mandarin</s_nm><s_cnt>2X</s_cnt><s_price>13,000</s_price></s_menu><s_total><s_total_price>26,000</s_\n",
+      "    Answer: <s_menu><s_nm>Honey Mandarin</s_nm><s_unitprice>13,000</s_unitprice><s_cnt>2 X</s_cnt><s_price>26,000</s_price></s_menu><s_total><s_total_price>26,000</s_total_price><s_cashprice>30,000</s_cashprice><s_changeprice>4,000</s_changeprice></s_total>\n",
+      " Normed ED: 0.5510204081632653\n",
+      "Prediction: <s_nm>KarageCurryTeishoku</s_nm><s_cnt>1</s_cnt><s_price>69,000</s_price><sep/><s_nm>Benton Plate</s_nm><s_cnt\n",
+      "    Answer: <s_menu><s_nm>KaraageCurryTeishoku</s_nm><s_cnt>1</s_cnt><s_price>69,000</s_price><sep/><s_nm>Lemon Plate</s_nm><s_cnt>1</s_cnt><s_price>19,000</s_price><sep/><s_nm>Ocha Hot</s_nm><s_cnt>1</s_cnt><s_price>15,000</s_price></s_menu><s_sub_total><s_subtotal_price>103,000</s_subtotal_price><s_service_price>7,725</s_service_price><s_tax_price>11,073</s_tax_price></s_sub_total><s_total><s_total_price>121,798</s_total_price><s_menutype_cnt>3</s_menutype_cnt><s_menuqty_cnt>3</s_menuqty_cnt></s_total>\n",
+      " Normed ED: 0.7847082494969819\n"
+     ]
+    }
+   ],
+   "source": [
+    "from lightning.pytorch.callbacks import Callback\n",
+    "from lightning.pytorch.loggers import WandbLogger\n",
+    "from lightning.pytorch.callbacks.early_stopping import EarlyStopping\n",
+    "\n",
+    "wandb_logger = WandbLogger(project=\"Idefics2\", name=\"demo-run-cord\")\n",
+    "\n",
+    "class PushToHubCallback(Callback):\n",
+    "    def on_train_epoch_end(self, trainer, pl_module):\n",
+    "        print(f\"Pushing model to the hub, epoch {trainer.current_epoch}\")\n",
+    "        pl_module.model.push_to_hub(\"nielsr/idefics2-cord-demo\",\n",
+    "                                    commit_message=f\"Training in progress, epoch {trainer.current_epoch}\")\n",
+    "\n",
+    "    def on_train_end(self, trainer, pl_module):\n",
+    "        print(f\"Pushing model to the hub after training\")\n",
+    "        pl_module.processor.push_to_hub(\"nielsr/idefics2-cord)demo\",\n",
+    "                                    commit_message=f\"Training done\")\n",
+    "        pl_module.model.push_to_hub(\"nielsr/donut-demo\",\n",
+    "                                    commit_message=f\"Training done\")\n",
+    "\n",
+    "early_stop_callback = EarlyStopping(monitor=\"val_edit_distance\", patience=3, verbose=False, mode=\"min\")\n",
+    "\n",
+    "trainer = L.Trainer(\n",
+    "        accelerator=\"gpu\",\n",
+    "        devices=1,\n",
+    "        max_epochs=config.get(\"max_epochs\"),\n",
+    "        val_check_interval=config.get(\"val_check_interval\"),\n",
+    "        check_val_every_n_epoch=config.get(\"check_val_every_n_epoch\"),\n",
+    "        gradient_clip_val=config.get(\"gradient_clip_val\"),\n",
+    "        precision=16, # we'll use mixed precision\n",
+    "        num_sanity_val_steps=0,\n",
+    "        logger=wandb_logger,\n",
+    "        callbacks=[PushToHubCallback(), early_stop_callback],\n",
+    ")\n",
+    "\n",
+    "trainer.fit(model_module)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/src/transformers/models/idefics2/modeling_idefics2.py b/src/transformers/models/idefics2/modeling_idefics2.py
index 28cd6155548ac7..58f4eb0aab2891 100644
--- a/src/transformers/models/idefics2/modeling_idefics2.py
+++ b/src/transformers/models/idefics2/modeling_idefics2.py
@@ -1348,9 +1348,6 @@ class Idefics2PreTrainedModel(PreTrainedModel):
     _supports_flash_attn_2 = True
 
     def _init_weights(self, module):
-        # important: this ported version of Idefics2 isn't meant for training from scratch - only
-        # inference and fine-tuning - so the proper init weights code has been removed - the original codebase
-        # https://github.com/haotian-liu/LLaVA/tree/main/idefics2 should serve for that purpose
         std = (
             self.config.text_config.initializer_range
             if hasattr(self.config, "initializer_range")
@@ -1442,13 +1439,13 @@ def _autoset_attn_implementation(
             Optionally, instead of passing `input_ids` you can choose to directly pass an embedded representation. This
             is useful if you want more control over how to convert `input_ids` indices into associated vectors than the
             model's internal embedding lookup matrix.
-        pixel_values (`torch.FloatTensor` of shape `(batch_size, num_channels, image_size, image_size)):
+        pixel_values (`torch.FloatTensor` of shape `(batch_size, num_patches, num_channels, height, width)):
             The tensors corresponding to the input images. Pixel values can be obtained using
-            [`AutoImageProcessor`]. See [`CLIPImageProcessor.__call__`] for details ([]`LlavaProcessor`] uses
-            [`CLIPImageProcessor`] for processing images).
-        pixel_attention_mask (`torch.Tensor` of shape `(batch_size, image_size, image_size)`, *optional*):
+            [`AutoImageProcessor`]. See [`Idefics2ImageProcessor.__call__`] for details ([]`Idefics2Processor`] uses
+            [`Idefics2ImageProcessor`] for processing images).
+        pixel_attention_mask (`torch.Tensor` of shape `(batch_size, num_patches, height, width)`, *optional*):
             Mask to avoid performing attention on padding pixel indices.
-        image_hidden_states (`torch.FloatTensor` of shape `(batch_size, num_channels, image_size, image_size)`):
+        image_hidden_states (`torch.FloatTensor` of shape `(batch_size, num_latents, hidden_size)`):
             The hidden states of the image encoder after modality projection and perceiver resampling.
         use_cache (`bool`, *optional*):
             If set to `True`, `past_key_values` key value states are returned and can be used to speed up decoding (see
diff --git a/src/transformers/models/idefics2/processing_idefics2.py b/src/transformers/models/idefics2/processing_idefics2.py
index 7b98519928f55e..bb08ee3ff0825e 100644
--- a/src/transformers/models/idefics2/processing_idefics2.py
+++ b/src/transformers/models/idefics2/processing_idefics2.py
@@ -118,8 +118,8 @@ def __call__(
         >>> from transformers import Idefics2Processor
         >>> from transformers.image_utils import load_image
 
-        >>> processor = Idefics2Processor.from_pretrained("HuggingFaceM4/idefics2-8b", image_seq_len=2)
-        >>> processor.image_processor.do_image_splitting = False  # Force as False to simplify the example
+        >>> # We specify `do_image_splitting=False` to reduce memory usage
+        >>> processor = Idefics2Processor.from_pretrained("HuggingFaceM4/idefics2-8b", image_seq_len=2, do_image_splitting=False)
 
         >>> url1 = "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
         >>> url2 = "https://cdn.britannica.com/59/94459-050-DBA42467/Skyline-Chicago.jpg"
diff --git a/src/transformers/models/idefics2/test.py b/src/transformers/models/idefics2/test.py
new file mode 100644
index 00000000000000..f71d79ce5e673f
--- /dev/null
+++ b/src/transformers/models/idefics2/test.py
@@ -0,0 +1,38 @@
+import requests
+from PIL import Image
+
+from transformers import Idefics2ForConditionalGeneration, Idefics2Processor
+
+
+url_1 = "http://images.cocodataset.org/val2017/000000039769.jpg"
+url_2 = "http://images.cocodataset.org/val2017/000000219578.jpg"
+
+image_1 = Image.open(requests.get(url_1, stream=True).raw)
+image_2 = Image.open(requests.get(url_2, stream=True).raw)
+images = [image_1, image_2]
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "text", "text": "What’s the difference between these two images?"},
+            {"type": "image"},
+            {"type": "image"},
+        ],
+    }
+]
+
+processor = Idefics2Processor.from_pretrained("HuggingFaceM4/idefics2-8b", do_image_splitting=False)
+model = Idefics2ForConditionalGeneration.from_pretrained("HuggingFaceM4/idefics2-8b", device_map="auto")
+
+# at inference time, one needs to pass `add_generation_prompt=True` in order to make sure the model completes the prompt
+text = processor.apply_chat_template(messages, add_generation_prompt=True)
+
+inputs = processor(images=images, text=text, return_tensors="pt").to("cuda")
+
+for k, v in inputs.items():
+    print(k, v.shape)
+
+generated_text = model.generate(**inputs, max_new_tokens=500)
+generated_text = processor.batch_decode(generated_text, skip_special_tokens=True)[0]
+print("Generated text:", generated_text)
diff --git a/src/transformers/models/idefics2/test_bis.py b/src/transformers/models/idefics2/test_bis.py
new file mode 100644
index 00000000000000..1928922a0ec8d1
--- /dev/null
+++ b/src/transformers/models/idefics2/test_bis.py
@@ -0,0 +1,27 @@
+import requests
+from PIL import Image
+
+from transformers import AutoProcessor
+
+
+processor = AutoProcessor.from_pretrained("HuggingFaceM4/idefics2-8b", do_image_splitting=False)
+
+url = "https://upload.wikimedia.org/wikipedia/commons/f/f3/Zinedine_Zidane_by_Tasnim_03.jpg"
+test_image = Image.open(requests.get(url, stream=True).raw)
+
+# prepare image and prompt for the model
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "text", "text": "Extract JSON."},
+            {"type": "image"},
+        ],
+    },
+]
+prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
+inputs = processor(text=prompt, images=[test_image], return_tensors="pt")
+for k, v in inputs.items():
+    print(k, v.shape)
+
+print(processor.batch_decode(inputs.input_ids))
diff --git a/src/transformers/models/idefics2/wandb/latest-run b/src/transformers/models/idefics2/wandb/latest-run
new file mode 120000
index 00000000000000..84f3d11f573af4
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/latest-run
@@ -0,0 +1 @@
+run-20240430_124040-t3hdwi09
\ No newline at end of file
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/files/config.yaml b/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/files/config.yaml
new file mode 100644
index 00000000000000..f388adc0a6b2e1
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/files/config.yaml
@@ -0,0 +1,58 @@
+wandb_version: 1
+
+_wandb:
+  desc: null
+  value:
+    python_version: 3.8.10
+    cli_version: 0.16.6
+    framework: huggingface
+    huggingface_version: 4.41.0.dev0
+    is_jupyter_run: true
+    is_kaggle_kernel: false
+    start_time: 1714461535.0
+    t:
+      1:
+      - 1
+      - 2
+      - 3
+      - 5
+      - 9
+      - 11
+      - 12
+      - 49
+      - 51
+      - 53
+      - 55
+      - 71
+      - 98
+      - 103
+      2:
+      - 1
+      - 2
+      - 3
+      - 5
+      - 9
+      - 11
+      - 12
+      - 49
+      - 51
+      - 53
+      - 55
+      - 71
+      - 98
+      - 103
+      3:
+      - 7
+      - 13
+      - 23
+      4: 3.8.10
+      5: 0.16.6
+      6: 4.41.0.dev0
+      8:
+      - 1
+      - 5
+      13: linux-x86_64
+    m:
+    - 1: trainer/global_step
+      6:
+      - 3
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/files/requirements.txt b/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/files/requirements.txt
new file mode 100644
index 00000000000000..9c0500b508e809
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/files/requirements.txt
@@ -0,0 +1,306 @@
+APScheduler==3.10.4
+Babel==2.14.0
+Flask==3.0.2
+GitPython==3.1.18
+Jinja2==3.1.3
+Levenshtein==0.25.1
+Mako==1.3.2
+Markdown==3.6
+MarkupSafe==2.1.5
+PyYAML==6.0.1
+Pygments==2.17.2
+SQLAlchemy==2.0.28
+SudachiDict-core==20240109
+SudachiPy==0.6.8
+Werkzeug==3.0.1
+absl-py==2.1.0
+accelerate==0.28.0
+aiohttp==3.9.3
+aiosignal==1.3.1
+alembic==1.13.1
+annotated-types==0.6.0
+appdirs==1.4.4
+arrow==1.3.0
+asttokens==2.4.1
+astunparse==1.6.3
+async-timeout==4.0.3
+attrs==23.2.0
+audioread==3.0.1
+av==9.2.0
+backcall==0.2.0
+backoff==1.11.1
+backports.zoneinfo==0.2.1
+beautifulsoup4==4.12.3
+bibtexparser==2.0.0b7
+binaryornot==0.4.4
+bitsandbytes==0.42.0
+black==24.3.0
+blinker==1.7.0
+cached-property==1.5.2
+cachetools==5.3.3
+certifi==2024.2.2
+cffi==1.16.0
+chardet==5.2.0
+charset-normalizer==3.3.2
+chex==0.1.7
+click==8.1.7
+clldutils==3.22.2
+cmake==3.28.3
+codecarbon==1.2.0
+colorama==0.4.6
+coloredlogs==15.0.1
+colorlog==6.8.2
+comm==0.2.2
+cookiecutter==1.7.3
+csvw==3.3.0
+dash-bootstrap-components==1.5.0
+dash-core-components==2.0.0
+dash-html-components==2.0.0
+dash-table==5.0.0
+dash==2.16.1
+datasets==2.18.0
+debugpy==1.8.1
+decorator==5.1.1
+decord==0.6.0
+dill==0.3.4
+dlinfo==1.2.1
+dm-tree==0.1.8
+docker-pycreds==0.4.0
+einops==0.7.0
+etils==1.3.0
+evaluate==0.4.1
+exceptiongroup==1.2.0
+execnet==2.0.2
+executing==2.0.1
+faiss-cpu==1.8.0
+fastjsonschema==2.19.1
+filelock==3.13.1
+fire==0.6.0
+flatbuffers==24.3.7
+flax==0.7.0
+frozenlist==1.4.1
+fsspec==2024.3.0
+fugashi==1.3.1
+gast==0.4.0
+gitdb==4.0.11
+google-auth-oauthlib==1.0.0
+google-auth==2.28.2
+google-pasta==0.2.0
+greenlet==3.0.3
+grpcio==1.62.1
+h5py==3.11.0
+hf-doc-builder==0.5.0
+huggingface-hub==0.21.4
+humanfriendly==10.0
+hypothesis==6.99.8
+idna==3.6
+importlib_metadata==7.0.2
+importlib_resources==6.3.1
+iniconfig==2.0.0
+ipadic==1.0.0
+ipykernel==6.29.4
+ipython==8.12.3
+isodate==0.6.1
+isort==5.13.2
+itsdangerous==2.1.2
+jax==0.4.13
+jaxlib==0.4.13
+jedi==0.19.1
+jinja2-time==0.2.0
+joblib==1.3.2
+jsonschema-specifications==2023.12.1
+jsonschema==4.21.1
+jupyter_client==8.6.1
+jupyter_core==5.7.2
+kenlm==0.2.0
+keras-core==0.1.5
+keras-nlp==0.6.1
+keras==2.13.1
+language-tags==1.2.0
+lazy_loader==0.3
+libclang==18.1.1
+librosa==0.10.1
+lightning-utilities==0.11.2
+lit==18.1.1
+llvmlite==0.41.1
+lxml==5.1.0
+markdown-it-py==3.0.0
+matplotlib-inline==0.1.7
+mdurl==0.1.2
+ml-dtypes==0.2.0
+mpmath==1.3.0
+msgpack==1.0.8
+multidict==6.0.5
+multiprocess==0.70.16
+mypy-extensions==1.0.0
+namex==0.0.8
+nbformat==5.10.3
+nest-asyncio==1.6.0
+networkx==3.1
+nltk==3.8.1
+numba==0.58.1
+numpy==1.24.4
+nvidia-cublas-cu11==11.10.3.66
+nvidia-cublas-cu12==12.1.3.1
+nvidia-cuda-cupti-cu11==11.7.101
+nvidia-cuda-cupti-cu12==12.1.105
+nvidia-cuda-nvrtc-cu11==11.7.99
+nvidia-cuda-nvrtc-cu12==12.1.105
+nvidia-cuda-runtime-cu11==11.7.99
+nvidia-cuda-runtime-cu12==12.1.105
+nvidia-cudnn-cu11==8.5.0.96
+nvidia-cudnn-cu12==8.9.2.26
+nvidia-cufft-cu11==10.9.0.58
+nvidia-cufft-cu12==11.0.2.54
+nvidia-curand-cu11==10.2.10.91
+nvidia-curand-cu12==10.3.2.106
+nvidia-cusolver-cu11==11.4.0.1
+nvidia-cusolver-cu12==11.4.5.107
+nvidia-cusparse-cu11==11.7.4.91
+nvidia-cusparse-cu12==12.1.0.106
+nvidia-nccl-cu11==2.14.3
+nvidia-nccl-cu12==2.20.5
+nvidia-nvjitlink-cu12==12.4.99
+nvidia-nvtx-cu11==11.7.91
+nvidia-nvtx-cu12==12.1.105
+oauthlib==3.2.2
+onnx==1.15.0
+onnxconverter-common==1.14.0
+onnxruntime-tools==1.7.0
+onnxruntime==1.16.3
+opt-einsum==3.3.0
+optax==0.1.4
+optuna==3.6.0
+orbax-checkpoint==0.2.3
+packaging==24.0
+pandas==2.0.3
+parameterized==0.9.0
+parso==0.8.4
+pathspec==0.12.1
+peft==0.10.0
+pexpect==4.9.0
+phonemizer==3.2.1
+pickleshare==0.7.5
+pillow==10.2.0
+pip==20.0.2
+pkg_resources==0.0.0
+pkgutil_resolve_name==1.3.10
+plac==1.4.3
+platformdirs==4.2.0
+plotly==5.20.0
+pluggy==1.4.0
+pooch==1.8.1
+portalocker==2.0.0
+poyo==0.5.0
+prompt-toolkit==3.0.43
+protobuf==4.25.3
+psutil==5.9.8
+ptyprocess==0.7.0
+pure-eval==0.2.2
+py-cpuinfo==9.0.0
+py3nvml==0.2.7
+pyarrow-hotfix==0.6
+pyarrow==15.0.1
+pyasn1-modules==0.3.0
+pyasn1==0.5.1
+pycparser==2.21
+pyctcdecode==0.5.0
+pydantic==2.6.4
+pydantic_core==2.16.3
+pygtrie==2.5.0
+pylatexenc==2.10
+pynvml==11.5.0
+pyparsing==3.1.2
+pypng==0.20220715.0
+pytest-timeout==2.3.1
+pytest-xdist==3.5.0
+pytest==7.4.4
+python-dateutil==2.9.0.post0
+python-slugify==8.0.4
+pytorch-lightning==2.2.3
+pytz==2024.1
+pyzmq==26.0.2
+rapidfuzz==3.8.1
+ray==2.9.3
+rdflib==7.0.0
+referencing==0.34.0
+regex==2023.12.25
+requests-oauthlib==1.4.0
+requests==2.31.0
+responses==0.18.0
+retrying==1.3.4
+rfc3986==1.5.0
+rhoknp==1.3.0
+rich==13.7.1
+rjieba==0.1.11
+rouge-score==0.1.2
+rpds-py==0.18.0
+rsa==4.9
+ruff==0.1.5
+sacrebleu==1.5.1
+sacremoses==0.1.1
+safetensors==0.4.2
+scikit-learn==1.3.2
+scipy==1.10.1
+segments==2.2.1
+sentencepiece==0.1.99
+sentry-sdk==2.0.1
+setproctitle==1.3.3
+setuptools==44.0.0
+sigopt==8.8.2
+six==1.16.0
+smmap==5.0.1
+sortedcontainers==2.4.0
+soundfile==0.12.1
+soupsieve==2.5
+soxr==0.3.7
+stack-data==0.6.3
+sympy==1.12
+tabulate==0.9.0
+tenacity==8.2.3
+tensorboard-data-server==0.7.2
+tensorboard==2.14.0
+tensorboardX==2.6.2.2
+tensorflow-estimator==2.13.0
+tensorflow-hub==0.16.1
+tensorflow-io-gcs-filesystem==0.34.0
+tensorflow-text==2.13.0
+tensorflow==2.13.1
+tensorstore==0.1.45
+termcolor==2.4.0
+text-unidecode==1.3
+tf2onnx==1.16.1
+tf_keras==2.15.1
+threadpoolctl==3.3.0
+timeout-decorator==0.5.0
+timm==0.9.16
+tokenizers==0.19.1
+tomli==2.0.1
+toolz==0.12.1
+torch==2.3.0
+torchaudio==2.1.2
+torchmetrics==1.3.2
+torchvision==0.18.0
+tornado==6.4
+tqdm==4.66.2
+traitlets==5.14.2
+transformers==4.41.0.dev0
+triton==2.3.0
+types-python-dateutil==2.9.0.20240316
+typing_extensions==4.10.0
+tzdata==2024.1
+tzlocal==5.2
+unidic-lite==1.0.8
+unidic==1.1.0
+uritemplate==4.1.1
+urllib3==1.26.18
+wandb==0.16.6
+wasabi==0.10.1
+wcwidth==0.2.13
+wheel==0.43.0
+wrapt==1.16.0
+xformers==0.0.22.post7
+xmltodict==0.13.0
+xxhash==3.4.1
+yarl==1.9.4
+zipp==3.18.1
\ No newline at end of file
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/files/wandb-metadata.json b/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/files/wandb-metadata.json
new file mode 100644
index 00000000000000..e28b4875f16d91
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/files/wandb-metadata.json
@@ -0,0 +1,703 @@
+{
+    "os": "Linux-5.4.0-166-generic-x86_64-with-glibc2.29",
+    "python": "3.8.10",
+    "heartbeatAt": "2024-04-30T07:18:55.849340",
+    "startedAt": "2024-04-30T07:18:55.163285",
+    "docker": null,
+    "cuda": null,
+    "args": [],
+    "state": "running",
+    "program": "<python with no main file>",
+    "codePathLocal": null,
+    "git": {
+        "remote": "git@github.com:NielsRogge/transformers.git",
+        "commit": "b794532fef67ad2ece05cfb504983ef76cd24f08"
+    },
+    "email": "niels.rogge1@gmail.com",
+    "root": "/home/niels/python_projects/transformers",
+    "host": "hf-dgx-01",
+    "username": "niels",
+    "executable": "/home/niels/python_projects/transformers/env/bin/python",
+    "cpu_count": 64,
+    "cpu_count_logical": 128,
+    "cpu_freq": {
+        "current": 2486.0019218750003,
+        "min": 1500.0,
+        "max": 2250.0
+    },
+    "cpu_freq_per_core": [
+        {
+            "current": 3267.516,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3270.823,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3265.242,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3281.016,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3264.948,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3273.113,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.62,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1689.157,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2399.842,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2354.78,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3237.882,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3291.941,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1636.381,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3266.2,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1635.641,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1638.544,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3279.859,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1889.79,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1636.975,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3264.014,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3265.078,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3275.907,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3126.734,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3264.993,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3272.368,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.656,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1635.79,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1638.488,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3280.23,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2428.724,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2364.214,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1635.998,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3267.796,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2281.893,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1989.929,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2305.238,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1640.678,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2183.398,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2241.726,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3278.783,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2142.262,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1638.711,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1638.456,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3264.444,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3270.976,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.525,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1636.91,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1636.756,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3262.078,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1676.115,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1639.357,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1622.436,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3266.68,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2245.016,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3266.47,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3268.124,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1546.657,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1553.958,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.219,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3263.907,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.134,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3266.913,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1549.011,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1556.62,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3275.794,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3274.676,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3270.156,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3275.157,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3266.754,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3275.375,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2123.271,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2186.738,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.842,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1991.91,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1629.332,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3263.79,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.686,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3255.912,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.448,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.242,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3262.619,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2201.728,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.348,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3257.616,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3258.482,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3254.205,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3257.062,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3262.794,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3261.239,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.854,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.718,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.122,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3263.092,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2218.45,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1994.986,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1630.486,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3271.66,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.976,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.762,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3255.157,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1688.142,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.897,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1752.091,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3262.871,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2194.616,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.369,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1629.919,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3255.245,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3256.658,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.372,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.91,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.473,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3267.894,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1836.147,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.211,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.449,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3286.487,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1664.18,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3265.422,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3124.3,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.847,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.459,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.187,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3258.696,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.723,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3265.47,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1673.331,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1573.322,
+            "min": 1500.0,
+            "max": 2250.0
+        }
+    ],
+    "disk": {
+        "/": {
+            "total": 1757.8785285949707,
+            "used": 1643.9329261779785
+        }
+    },
+    "gpu": "NVIDIA A100-SXM4-80GB",
+    "gpu_count": 5,
+    "gpu_devices": [
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA DGX Display",
+            "memory_total": 4294967296
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        }
+    ],
+    "memory": {
+        "total": 503.5396919250488
+    }
+}
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/run-0w9d9xlt.wandb b/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/run-0w9d9xlt.wandb
new file mode 100644
index 00000000000000..efa39717d90d23
Binary files /dev/null and b/src/transformers/models/idefics2/wandb/run-20240430_091855-0w9d9xlt/run-0w9d9xlt.wandb differ
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/files/config.yaml b/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/files/config.yaml
new file mode 100644
index 00000000000000..504c98560a679c
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/files/config.yaml
@@ -0,0 +1,58 @@
+wandb_version: 1
+
+_wandb:
+  desc: null
+  value:
+    python_version: 3.8.10
+    cli_version: 0.16.6
+    framework: huggingface
+    huggingface_version: 4.41.0.dev0
+    is_jupyter_run: true
+    is_kaggle_kernel: false
+    start_time: 1714462726.0
+    t:
+      1:
+      - 1
+      - 2
+      - 3
+      - 5
+      - 9
+      - 11
+      - 12
+      - 49
+      - 51
+      - 53
+      - 55
+      - 71
+      - 98
+      - 103
+      2:
+      - 1
+      - 2
+      - 3
+      - 5
+      - 9
+      - 11
+      - 12
+      - 49
+      - 51
+      - 53
+      - 55
+      - 71
+      - 98
+      - 103
+      3:
+      - 7
+      - 13
+      - 23
+      4: 3.8.10
+      5: 0.16.6
+      6: 4.41.0.dev0
+      8:
+      - 1
+      - 5
+      13: linux-x86_64
+    m:
+    - 1: trainer/global_step
+      6:
+      - 3
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/files/requirements.txt b/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/files/requirements.txt
new file mode 100644
index 00000000000000..f79e27fbf99175
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/files/requirements.txt
@@ -0,0 +1,307 @@
+APScheduler==3.10.4
+Babel==2.14.0
+Flask==3.0.2
+GitPython==3.1.18
+Jinja2==3.1.3
+Levenshtein==0.25.1
+Mako==1.3.2
+Markdown==3.6
+MarkupSafe==2.1.5
+PyYAML==6.0.1
+Pygments==2.17.2
+SQLAlchemy==2.0.28
+SudachiDict-core==20240109
+SudachiPy==0.6.8
+Werkzeug==3.0.1
+absl-py==2.1.0
+accelerate==0.28.0
+aiohttp==3.9.3
+aiosignal==1.3.1
+alembic==1.13.1
+annotated-types==0.6.0
+appdirs==1.4.4
+arrow==1.3.0
+asttokens==2.4.1
+astunparse==1.6.3
+async-timeout==4.0.3
+attrs==23.2.0
+audioread==3.0.1
+av==9.2.0
+backcall==0.2.0
+backoff==1.11.1
+backports.zoneinfo==0.2.1
+beautifulsoup4==4.12.3
+bibtexparser==2.0.0b7
+binaryornot==0.4.4
+bitsandbytes==0.42.0
+black==24.3.0
+blinker==1.7.0
+cached-property==1.5.2
+cachetools==5.3.3
+certifi==2024.2.2
+cffi==1.16.0
+chardet==5.2.0
+charset-normalizer==3.3.2
+chex==0.1.7
+click==8.1.7
+clldutils==3.22.2
+cmake==3.28.3
+codecarbon==1.2.0
+colorama==0.4.6
+coloredlogs==15.0.1
+colorlog==6.8.2
+comm==0.2.2
+cookiecutter==1.7.3
+csvw==3.3.0
+dash-bootstrap-components==1.5.0
+dash-core-components==2.0.0
+dash-html-components==2.0.0
+dash-table==5.0.0
+dash==2.16.1
+datasets==2.18.0
+debugpy==1.8.1
+decorator==5.1.1
+decord==0.6.0
+dill==0.3.4
+dlinfo==1.2.1
+dm-tree==0.1.8
+docker-pycreds==0.4.0
+einops==0.7.0
+etils==1.3.0
+evaluate==0.4.1
+exceptiongroup==1.2.0
+execnet==2.0.2
+executing==2.0.1
+faiss-cpu==1.8.0
+fastjsonschema==2.19.1
+filelock==3.13.1
+fire==0.6.0
+flatbuffers==24.3.7
+flax==0.7.0
+frozenlist==1.4.1
+fsspec==2024.3.0
+fugashi==1.3.1
+gast==0.4.0
+gitdb==4.0.11
+google-auth-oauthlib==1.0.0
+google-auth==2.28.2
+google-pasta==0.2.0
+greenlet==3.0.3
+grpcio==1.62.1
+h5py==3.11.0
+hf-doc-builder==0.5.0
+huggingface-hub==0.21.4
+humanfriendly==10.0
+hypothesis==6.99.8
+idna==3.6
+importlib_metadata==7.0.2
+importlib_resources==6.3.1
+iniconfig==2.0.0
+ipadic==1.0.0
+ipykernel==6.29.4
+ipython==8.12.3
+isodate==0.6.1
+isort==5.13.2
+itsdangerous==2.1.2
+jax==0.4.13
+jaxlib==0.4.13
+jedi==0.19.1
+jinja2-time==0.2.0
+joblib==1.3.2
+jsonschema-specifications==2023.12.1
+jsonschema==4.21.1
+jupyter_client==8.6.1
+jupyter_core==5.7.2
+kenlm==0.2.0
+keras-core==0.1.5
+keras-nlp==0.6.1
+keras==2.13.1
+language-tags==1.2.0
+lazy_loader==0.3
+libclang==18.1.1
+librosa==0.10.1
+lightning-utilities==0.11.2
+lightning==2.2.3
+lit==18.1.1
+llvmlite==0.41.1
+lxml==5.1.0
+markdown-it-py==3.0.0
+matplotlib-inline==0.1.7
+mdurl==0.1.2
+ml-dtypes==0.2.0
+mpmath==1.3.0
+msgpack==1.0.8
+multidict==6.0.5
+multiprocess==0.70.16
+mypy-extensions==1.0.0
+namex==0.0.8
+nbformat==5.10.3
+nest-asyncio==1.6.0
+networkx==3.1
+nltk==3.8.1
+numba==0.58.1
+numpy==1.24.4
+nvidia-cublas-cu11==11.10.3.66
+nvidia-cublas-cu12==12.1.3.1
+nvidia-cuda-cupti-cu11==11.7.101
+nvidia-cuda-cupti-cu12==12.1.105
+nvidia-cuda-nvrtc-cu11==11.7.99
+nvidia-cuda-nvrtc-cu12==12.1.105
+nvidia-cuda-runtime-cu11==11.7.99
+nvidia-cuda-runtime-cu12==12.1.105
+nvidia-cudnn-cu11==8.5.0.96
+nvidia-cudnn-cu12==8.9.2.26
+nvidia-cufft-cu11==10.9.0.58
+nvidia-cufft-cu12==11.0.2.54
+nvidia-curand-cu11==10.2.10.91
+nvidia-curand-cu12==10.3.2.106
+nvidia-cusolver-cu11==11.4.0.1
+nvidia-cusolver-cu12==11.4.5.107
+nvidia-cusparse-cu11==11.7.4.91
+nvidia-cusparse-cu12==12.1.0.106
+nvidia-nccl-cu11==2.14.3
+nvidia-nccl-cu12==2.20.5
+nvidia-nvjitlink-cu12==12.4.99
+nvidia-nvtx-cu11==11.7.91
+nvidia-nvtx-cu12==12.1.105
+oauthlib==3.2.2
+onnx==1.15.0
+onnxconverter-common==1.14.0
+onnxruntime-tools==1.7.0
+onnxruntime==1.16.3
+opt-einsum==3.3.0
+optax==0.1.4
+optuna==3.6.0
+orbax-checkpoint==0.2.3
+packaging==24.0
+pandas==2.0.3
+parameterized==0.9.0
+parso==0.8.4
+pathspec==0.12.1
+peft==0.10.0
+pexpect==4.9.0
+phonemizer==3.2.1
+pickleshare==0.7.5
+pillow==10.2.0
+pip==20.0.2
+pkg_resources==0.0.0
+pkgutil_resolve_name==1.3.10
+plac==1.4.3
+platformdirs==4.2.0
+plotly==5.20.0
+pluggy==1.4.0
+pooch==1.8.1
+portalocker==2.0.0
+poyo==0.5.0
+prompt-toolkit==3.0.43
+protobuf==4.25.3
+psutil==5.9.8
+ptyprocess==0.7.0
+pure-eval==0.2.2
+py-cpuinfo==9.0.0
+py3nvml==0.2.7
+pyarrow-hotfix==0.6
+pyarrow==15.0.1
+pyasn1-modules==0.3.0
+pyasn1==0.5.1
+pycparser==2.21
+pyctcdecode==0.5.0
+pydantic==2.6.4
+pydantic_core==2.16.3
+pygtrie==2.5.0
+pylatexenc==2.10
+pynvml==11.5.0
+pyparsing==3.1.2
+pypng==0.20220715.0
+pytest-timeout==2.3.1
+pytest-xdist==3.5.0
+pytest==7.4.4
+python-dateutil==2.9.0.post0
+python-slugify==8.0.4
+pytorch-lightning==2.2.3
+pytz==2024.1
+pyzmq==26.0.2
+rapidfuzz==3.8.1
+ray==2.9.3
+rdflib==7.0.0
+referencing==0.34.0
+regex==2023.12.25
+requests-oauthlib==1.4.0
+requests==2.31.0
+responses==0.18.0
+retrying==1.3.4
+rfc3986==1.5.0
+rhoknp==1.3.0
+rich==13.7.1
+rjieba==0.1.11
+rouge-score==0.1.2
+rpds-py==0.18.0
+rsa==4.9
+ruff==0.1.5
+sacrebleu==1.5.1
+sacremoses==0.1.1
+safetensors==0.4.2
+scikit-learn==1.3.2
+scipy==1.10.1
+segments==2.2.1
+sentencepiece==0.1.99
+sentry-sdk==2.0.1
+setproctitle==1.3.3
+setuptools==44.0.0
+sigopt==8.8.2
+six==1.16.0
+smmap==5.0.1
+sortedcontainers==2.4.0
+soundfile==0.12.1
+soupsieve==2.5
+soxr==0.3.7
+stack-data==0.6.3
+sympy==1.12
+tabulate==0.9.0
+tenacity==8.2.3
+tensorboard-data-server==0.7.2
+tensorboard==2.14.0
+tensorboardX==2.6.2.2
+tensorflow-estimator==2.13.0
+tensorflow-hub==0.16.1
+tensorflow-io-gcs-filesystem==0.34.0
+tensorflow-text==2.13.0
+tensorflow==2.13.1
+tensorstore==0.1.45
+termcolor==2.4.0
+text-unidecode==1.3
+tf2onnx==1.16.1
+tf_keras==2.15.1
+threadpoolctl==3.3.0
+timeout-decorator==0.5.0
+timm==0.9.16
+tokenizers==0.19.1
+tomli==2.0.1
+toolz==0.12.1
+torch==2.3.0
+torchaudio==2.1.2
+torchmetrics==1.3.2
+torchvision==0.18.0
+tornado==6.4
+tqdm==4.66.2
+traitlets==5.14.2
+transformers==4.41.0.dev0
+triton==2.3.0
+types-python-dateutil==2.9.0.20240316
+typing_extensions==4.10.0
+tzdata==2024.1
+tzlocal==5.2
+unidic-lite==1.0.8
+unidic==1.1.0
+uritemplate==4.1.1
+urllib3==1.26.18
+wandb==0.16.6
+wasabi==0.10.1
+wcwidth==0.2.13
+wheel==0.43.0
+wrapt==1.16.0
+xformers==0.0.22.post7
+xmltodict==0.13.0
+xxhash==3.4.1
+yarl==1.9.4
+zipp==3.18.1
\ No newline at end of file
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/files/wandb-metadata.json b/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/files/wandb-metadata.json
new file mode 100644
index 00000000000000..b68095fcbac751
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/files/wandb-metadata.json
@@ -0,0 +1,703 @@
+{
+    "os": "Linux-5.4.0-166-generic-x86_64-with-glibc2.29",
+    "python": "3.8.10",
+    "heartbeatAt": "2024-04-30T07:38:46.874230",
+    "startedAt": "2024-04-30T07:38:46.128256",
+    "docker": null,
+    "cuda": null,
+    "args": [],
+    "state": "running",
+    "program": "<python with no main file>",
+    "codePathLocal": null,
+    "git": {
+        "remote": "git@github.com:NielsRogge/transformers.git",
+        "commit": "b794532fef67ad2ece05cfb504983ef76cd24f08"
+    },
+    "email": "niels.rogge1@gmail.com",
+    "root": "/home/niels/python_projects/transformers",
+    "host": "hf-dgx-01",
+    "username": "niels",
+    "executable": "/home/niels/python_projects/transformers/env/bin/python",
+    "cpu_count": 64,
+    "cpu_count_logical": 128,
+    "cpu_freq": {
+        "current": 2260.5603593749997,
+        "min": 1500.0,
+        "max": 2250.0
+    },
+    "cpu_freq_per_core": [
+        {
+            "current": 3293.257,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.619,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1642.696,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.381,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3281.737,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1641.368,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.824,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.25,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3280.069,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.083,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3276.561,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.977,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.131,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3293.061,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3283.703,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.933,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3285.291,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.851,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3199.14,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.366,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.891,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3291.193,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.212,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.806,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.507,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.98,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.962,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3282.619,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.745,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.243,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3284.222,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.968,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.193,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3283.865,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2156.243,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.067,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1647.016,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3279.841,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3292.037,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2176.502,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.441,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.717,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.098,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3285.099,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1703.344,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.387,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.687,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3290.489,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3281.652,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3288.547,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.362,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2159.969,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3284.02,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1929.8,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.039,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1642.621,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2301.431,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1731.327,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1774.1,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2640.429,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3297.246,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.784,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.272,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.799,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3283.651,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.61,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1647.573,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.665,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3299.517,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.785,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.848,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1757.714,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3289.268,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.474,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2779.172,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.714,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1647.329,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3283.964,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3296.812,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.877,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3293.616,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.179,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2233.211,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.247,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.402,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3284.078,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.068,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.267,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2163.916,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.032,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.853,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3296.469,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.044,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1642.211,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3286.49,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.061,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1642.78,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3298.218,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1665.988,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.226,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.321,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3285.514,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3297.003,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1713.823,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.321,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1695.646,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.141,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3295.811,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.42,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.313,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.436,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2196.683,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3279.45,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2053.204,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1984.948,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1718.551,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3289.541,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3155.855,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2161.777,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2027.994,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1693.131,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2280.921,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2285.889,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2739.695,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3280.425,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2144.284,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1661.353,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1720.485,
+            "min": 1500.0,
+            "max": 2250.0
+        }
+    ],
+    "disk": {
+        "/": {
+            "total": 1757.8785285949707,
+            "used": 1643.9480934143066
+        }
+    },
+    "gpu": "NVIDIA A100-SXM4-80GB",
+    "gpu_count": 5,
+    "gpu_devices": [
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA DGX Display",
+            "memory_total": 4294967296
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        }
+    ],
+    "memory": {
+        "total": 503.5396919250488
+    }
+}
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/run-prlaj2s9.wandb b/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/run-prlaj2s9.wandb
new file mode 100644
index 00000000000000..6c359a2aa953cf
Binary files /dev/null and b/src/transformers/models/idefics2/wandb/run-20240430_093846-prlaj2s9/run-prlaj2s9.wandb differ
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/config.yaml b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/config.yaml
new file mode 100644
index 00000000000000..78e14ebc9d0fe2
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/config.yaml
@@ -0,0 +1,62 @@
+wandb_version: 1
+
+_wandb:
+  desc: null
+  value:
+    python_version: 3.8.10
+    cli_version: 0.16.6
+    framework: huggingface
+    huggingface_version: 4.41.0.dev0
+    is_jupyter_run: true
+    is_kaggle_kernel: false
+    start_time: 1714471660.0
+    t:
+      1:
+      - 1
+      - 2
+      - 3
+      - 5
+      - 11
+      - 12
+      - 49
+      - 51
+      - 53
+      - 55
+      - 71
+      - 98
+      2:
+      - 1
+      - 2
+      - 3
+      - 5
+      - 11
+      - 12
+      - 49
+      - 51
+      - 53
+      - 55
+      - 71
+      - 98
+      3:
+      - 7
+      - 13
+      - 23
+      4: 3.8.10
+      5: 0.16.6
+      6: 4.41.0.dev0
+      8:
+      - 1
+      - 5
+      13: linux-x86_64
+    m:
+    - 1: trainer/global_step
+      6:
+      - 3
+    - 1: train_loss
+      5: 1
+      6:
+      - 1
+    - 1: epoch
+      5: 1
+      6:
+      - 1
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/requirements.txt b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/requirements.txt
new file mode 100644
index 00000000000000..f79e27fbf99175
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/requirements.txt
@@ -0,0 +1,307 @@
+APScheduler==3.10.4
+Babel==2.14.0
+Flask==3.0.2
+GitPython==3.1.18
+Jinja2==3.1.3
+Levenshtein==0.25.1
+Mako==1.3.2
+Markdown==3.6
+MarkupSafe==2.1.5
+PyYAML==6.0.1
+Pygments==2.17.2
+SQLAlchemy==2.0.28
+SudachiDict-core==20240109
+SudachiPy==0.6.8
+Werkzeug==3.0.1
+absl-py==2.1.0
+accelerate==0.28.0
+aiohttp==3.9.3
+aiosignal==1.3.1
+alembic==1.13.1
+annotated-types==0.6.0
+appdirs==1.4.4
+arrow==1.3.0
+asttokens==2.4.1
+astunparse==1.6.3
+async-timeout==4.0.3
+attrs==23.2.0
+audioread==3.0.1
+av==9.2.0
+backcall==0.2.0
+backoff==1.11.1
+backports.zoneinfo==0.2.1
+beautifulsoup4==4.12.3
+bibtexparser==2.0.0b7
+binaryornot==0.4.4
+bitsandbytes==0.42.0
+black==24.3.0
+blinker==1.7.0
+cached-property==1.5.2
+cachetools==5.3.3
+certifi==2024.2.2
+cffi==1.16.0
+chardet==5.2.0
+charset-normalizer==3.3.2
+chex==0.1.7
+click==8.1.7
+clldutils==3.22.2
+cmake==3.28.3
+codecarbon==1.2.0
+colorama==0.4.6
+coloredlogs==15.0.1
+colorlog==6.8.2
+comm==0.2.2
+cookiecutter==1.7.3
+csvw==3.3.0
+dash-bootstrap-components==1.5.0
+dash-core-components==2.0.0
+dash-html-components==2.0.0
+dash-table==5.0.0
+dash==2.16.1
+datasets==2.18.0
+debugpy==1.8.1
+decorator==5.1.1
+decord==0.6.0
+dill==0.3.4
+dlinfo==1.2.1
+dm-tree==0.1.8
+docker-pycreds==0.4.0
+einops==0.7.0
+etils==1.3.0
+evaluate==0.4.1
+exceptiongroup==1.2.0
+execnet==2.0.2
+executing==2.0.1
+faiss-cpu==1.8.0
+fastjsonschema==2.19.1
+filelock==3.13.1
+fire==0.6.0
+flatbuffers==24.3.7
+flax==0.7.0
+frozenlist==1.4.1
+fsspec==2024.3.0
+fugashi==1.3.1
+gast==0.4.0
+gitdb==4.0.11
+google-auth-oauthlib==1.0.0
+google-auth==2.28.2
+google-pasta==0.2.0
+greenlet==3.0.3
+grpcio==1.62.1
+h5py==3.11.0
+hf-doc-builder==0.5.0
+huggingface-hub==0.21.4
+humanfriendly==10.0
+hypothesis==6.99.8
+idna==3.6
+importlib_metadata==7.0.2
+importlib_resources==6.3.1
+iniconfig==2.0.0
+ipadic==1.0.0
+ipykernel==6.29.4
+ipython==8.12.3
+isodate==0.6.1
+isort==5.13.2
+itsdangerous==2.1.2
+jax==0.4.13
+jaxlib==0.4.13
+jedi==0.19.1
+jinja2-time==0.2.0
+joblib==1.3.2
+jsonschema-specifications==2023.12.1
+jsonschema==4.21.1
+jupyter_client==8.6.1
+jupyter_core==5.7.2
+kenlm==0.2.0
+keras-core==0.1.5
+keras-nlp==0.6.1
+keras==2.13.1
+language-tags==1.2.0
+lazy_loader==0.3
+libclang==18.1.1
+librosa==0.10.1
+lightning-utilities==0.11.2
+lightning==2.2.3
+lit==18.1.1
+llvmlite==0.41.1
+lxml==5.1.0
+markdown-it-py==3.0.0
+matplotlib-inline==0.1.7
+mdurl==0.1.2
+ml-dtypes==0.2.0
+mpmath==1.3.0
+msgpack==1.0.8
+multidict==6.0.5
+multiprocess==0.70.16
+mypy-extensions==1.0.0
+namex==0.0.8
+nbformat==5.10.3
+nest-asyncio==1.6.0
+networkx==3.1
+nltk==3.8.1
+numba==0.58.1
+numpy==1.24.4
+nvidia-cublas-cu11==11.10.3.66
+nvidia-cublas-cu12==12.1.3.1
+nvidia-cuda-cupti-cu11==11.7.101
+nvidia-cuda-cupti-cu12==12.1.105
+nvidia-cuda-nvrtc-cu11==11.7.99
+nvidia-cuda-nvrtc-cu12==12.1.105
+nvidia-cuda-runtime-cu11==11.7.99
+nvidia-cuda-runtime-cu12==12.1.105
+nvidia-cudnn-cu11==8.5.0.96
+nvidia-cudnn-cu12==8.9.2.26
+nvidia-cufft-cu11==10.9.0.58
+nvidia-cufft-cu12==11.0.2.54
+nvidia-curand-cu11==10.2.10.91
+nvidia-curand-cu12==10.3.2.106
+nvidia-cusolver-cu11==11.4.0.1
+nvidia-cusolver-cu12==11.4.5.107
+nvidia-cusparse-cu11==11.7.4.91
+nvidia-cusparse-cu12==12.1.0.106
+nvidia-nccl-cu11==2.14.3
+nvidia-nccl-cu12==2.20.5
+nvidia-nvjitlink-cu12==12.4.99
+nvidia-nvtx-cu11==11.7.91
+nvidia-nvtx-cu12==12.1.105
+oauthlib==3.2.2
+onnx==1.15.0
+onnxconverter-common==1.14.0
+onnxruntime-tools==1.7.0
+onnxruntime==1.16.3
+opt-einsum==3.3.0
+optax==0.1.4
+optuna==3.6.0
+orbax-checkpoint==0.2.3
+packaging==24.0
+pandas==2.0.3
+parameterized==0.9.0
+parso==0.8.4
+pathspec==0.12.1
+peft==0.10.0
+pexpect==4.9.0
+phonemizer==3.2.1
+pickleshare==0.7.5
+pillow==10.2.0
+pip==20.0.2
+pkg_resources==0.0.0
+pkgutil_resolve_name==1.3.10
+plac==1.4.3
+platformdirs==4.2.0
+plotly==5.20.0
+pluggy==1.4.0
+pooch==1.8.1
+portalocker==2.0.0
+poyo==0.5.0
+prompt-toolkit==3.0.43
+protobuf==4.25.3
+psutil==5.9.8
+ptyprocess==0.7.0
+pure-eval==0.2.2
+py-cpuinfo==9.0.0
+py3nvml==0.2.7
+pyarrow-hotfix==0.6
+pyarrow==15.0.1
+pyasn1-modules==0.3.0
+pyasn1==0.5.1
+pycparser==2.21
+pyctcdecode==0.5.0
+pydantic==2.6.4
+pydantic_core==2.16.3
+pygtrie==2.5.0
+pylatexenc==2.10
+pynvml==11.5.0
+pyparsing==3.1.2
+pypng==0.20220715.0
+pytest-timeout==2.3.1
+pytest-xdist==3.5.0
+pytest==7.4.4
+python-dateutil==2.9.0.post0
+python-slugify==8.0.4
+pytorch-lightning==2.2.3
+pytz==2024.1
+pyzmq==26.0.2
+rapidfuzz==3.8.1
+ray==2.9.3
+rdflib==7.0.0
+referencing==0.34.0
+regex==2023.12.25
+requests-oauthlib==1.4.0
+requests==2.31.0
+responses==0.18.0
+retrying==1.3.4
+rfc3986==1.5.0
+rhoknp==1.3.0
+rich==13.7.1
+rjieba==0.1.11
+rouge-score==0.1.2
+rpds-py==0.18.0
+rsa==4.9
+ruff==0.1.5
+sacrebleu==1.5.1
+sacremoses==0.1.1
+safetensors==0.4.2
+scikit-learn==1.3.2
+scipy==1.10.1
+segments==2.2.1
+sentencepiece==0.1.99
+sentry-sdk==2.0.1
+setproctitle==1.3.3
+setuptools==44.0.0
+sigopt==8.8.2
+six==1.16.0
+smmap==5.0.1
+sortedcontainers==2.4.0
+soundfile==0.12.1
+soupsieve==2.5
+soxr==0.3.7
+stack-data==0.6.3
+sympy==1.12
+tabulate==0.9.0
+tenacity==8.2.3
+tensorboard-data-server==0.7.2
+tensorboard==2.14.0
+tensorboardX==2.6.2.2
+tensorflow-estimator==2.13.0
+tensorflow-hub==0.16.1
+tensorflow-io-gcs-filesystem==0.34.0
+tensorflow-text==2.13.0
+tensorflow==2.13.1
+tensorstore==0.1.45
+termcolor==2.4.0
+text-unidecode==1.3
+tf2onnx==1.16.1
+tf_keras==2.15.1
+threadpoolctl==3.3.0
+timeout-decorator==0.5.0
+timm==0.9.16
+tokenizers==0.19.1
+tomli==2.0.1
+toolz==0.12.1
+torch==2.3.0
+torchaudio==2.1.2
+torchmetrics==1.3.2
+torchvision==0.18.0
+tornado==6.4
+tqdm==4.66.2
+traitlets==5.14.2
+transformers==4.41.0.dev0
+triton==2.3.0
+types-python-dateutil==2.9.0.20240316
+typing_extensions==4.10.0
+tzdata==2024.1
+tzlocal==5.2
+unidic-lite==1.0.8
+unidic==1.1.0
+uritemplate==4.1.1
+urllib3==1.26.18
+wandb==0.16.6
+wasabi==0.10.1
+wcwidth==0.2.13
+wheel==0.43.0
+wrapt==1.16.0
+xformers==0.0.22.post7
+xmltodict==0.13.0
+xxhash==3.4.1
+yarl==1.9.4
+zipp==3.18.1
\ No newline at end of file
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/wandb-metadata.json b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/wandb-metadata.json
new file mode 100644
index 00000000000000..1feaeedaf99c25
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/wandb-metadata.json
@@ -0,0 +1,703 @@
+{
+    "os": "Linux-5.4.0-166-generic-x86_64-with-glibc2.29",
+    "python": "3.8.10",
+    "heartbeatAt": "2024-04-30T10:07:41.645094",
+    "startedAt": "2024-04-30T10:07:40.970500",
+    "docker": null,
+    "cuda": null,
+    "args": [],
+    "state": "running",
+    "program": "<python with no main file>",
+    "codePathLocal": null,
+    "git": {
+        "remote": "git@github.com:NielsRogge/transformers.git",
+        "commit": "20a1cfa3db5bb5d96725d619a293500a81de0bc6"
+    },
+    "email": "niels.rogge1@gmail.com",
+    "root": "/home/niels/python_projects/transformers",
+    "host": "hf-dgx-01",
+    "username": "niels",
+    "executable": "/home/niels/python_projects/transformers/env/bin/python",
+    "cpu_count": 64,
+    "cpu_count_logical": 128,
+    "cpu_freq": {
+        "current": 2296.4624374999994,
+        "min": 1500.0,
+        "max": 2250.0
+    },
+    "cpu_freq_per_core": [
+        {
+            "current": 3270.243,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2258.021,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.702,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3308.325,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.339,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3279.169,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2185.469,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1664.269,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3285.146,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.745,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.974,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3289.931,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.382,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3292.799,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.079,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.234,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2148.386,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.93,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3279.711,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.775,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1673.221,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1642.602,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3292.191,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.519,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3278.846,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.492,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.984,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.704,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1708.665,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1707.002,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1949.356,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2351.421,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2432.55,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.791,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3286.429,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1642.533,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3288.869,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.2,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2292.926,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.728,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3271.923,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.024,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1647.888,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2895.577,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3272.423,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.855,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.518,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.6,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1954.402,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.611,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.29,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3269.275,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3273.733,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.38,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.342,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1643.159,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2291.926,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1711.177,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2435.85,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1704.652,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1646.497,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3273.645,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.366,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1837.308,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3272.962,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2325.155,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.783,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3284.115,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.512,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3295.013,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2273.35,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2150.698,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3273.126,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.959,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1635.358,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3272.046,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.641,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3277.674,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.243,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.267,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2862.147,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2828.998,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3272.298,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2945.001,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3047.366,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1715.297,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3272.452,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2070.978,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3266.589,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2120.919,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3247.007,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3271.258,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1819.614,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1728.017,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3257.389,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2173.478,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1678.57,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.148,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3278.917,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1676.822,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3276.474,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.715,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.016,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1630.956,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3261.95,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3076.884,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1630.801,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.077,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3259.796,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.969,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.441,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1630.95,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2141.263,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.148,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1679.228,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3264.692,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3271.754,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.456,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.525,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.224,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3281.607,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1777.97,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1650.754,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1781.772,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.825,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3264.092,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.408,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3253.546,
+            "min": 1500.0,
+            "max": 2250.0
+        }
+    ],
+    "disk": {
+        "/": {
+            "total": 1757.8785285949707,
+            "used": 1616.2449836730957
+        }
+    },
+    "gpu": "NVIDIA A100-SXM4-80GB",
+    "gpu_count": 5,
+    "gpu_devices": [
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA DGX Display",
+            "memory_total": 4294967296
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        }
+    ],
+    "memory": {
+        "total": 503.5396919250488
+    }
+}
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/wandb-summary.json b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/wandb-summary.json
new file mode 100644
index 00000000000000..2b996351d772a6
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/files/wandb-summary.json
@@ -0,0 +1 @@
+{"train_loss": 7.635411020601168e-05, "epoch": 0, "trainer/global_step": 49, "_timestamp": 1714471726.2381043, "_runtime": 65.26272630691528, "_step": 0}
\ No newline at end of file
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/run-z6z7tlgg.wandb b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/run-z6z7tlgg.wandb
new file mode 100644
index 00000000000000..23220915c1f132
Binary files /dev/null and b/src/transformers/models/idefics2/wandb/run-20240430_120740-z6z7tlgg/run-z6z7tlgg.wandb differ
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/config.yaml b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/config.yaml
new file mode 100644
index 00000000000000..f4b99fb4a5cb19
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/config.yaml
@@ -0,0 +1,62 @@
+wandb_version: 1
+
+_wandb:
+  desc: null
+  value:
+    python_version: 3.8.10
+    cli_version: 0.16.6
+    framework: huggingface
+    huggingface_version: 4.41.0.dev0
+    is_jupyter_run: true
+    is_kaggle_kernel: false
+    start_time: 1714473640.0
+    t:
+      1:
+      - 1
+      - 2
+      - 3
+      - 5
+      - 11
+      - 12
+      - 49
+      - 51
+      - 53
+      - 55
+      - 71
+      - 98
+      2:
+      - 1
+      - 2
+      - 3
+      - 5
+      - 11
+      - 12
+      - 49
+      - 51
+      - 53
+      - 55
+      - 71
+      - 98
+      3:
+      - 7
+      - 13
+      - 23
+      4: 3.8.10
+      5: 0.16.6
+      6: 4.41.0.dev0
+      8:
+      - 1
+      - 5
+      13: linux-x86_64
+    m:
+    - 1: trainer/global_step
+      6:
+      - 3
+    - 1: train_loss
+      5: 1
+      6:
+      - 1
+    - 1: epoch
+      5: 1
+      6:
+      - 1
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/requirements.txt b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/requirements.txt
new file mode 100644
index 00000000000000..f79e27fbf99175
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/requirements.txt
@@ -0,0 +1,307 @@
+APScheduler==3.10.4
+Babel==2.14.0
+Flask==3.0.2
+GitPython==3.1.18
+Jinja2==3.1.3
+Levenshtein==0.25.1
+Mako==1.3.2
+Markdown==3.6
+MarkupSafe==2.1.5
+PyYAML==6.0.1
+Pygments==2.17.2
+SQLAlchemy==2.0.28
+SudachiDict-core==20240109
+SudachiPy==0.6.8
+Werkzeug==3.0.1
+absl-py==2.1.0
+accelerate==0.28.0
+aiohttp==3.9.3
+aiosignal==1.3.1
+alembic==1.13.1
+annotated-types==0.6.0
+appdirs==1.4.4
+arrow==1.3.0
+asttokens==2.4.1
+astunparse==1.6.3
+async-timeout==4.0.3
+attrs==23.2.0
+audioread==3.0.1
+av==9.2.0
+backcall==0.2.0
+backoff==1.11.1
+backports.zoneinfo==0.2.1
+beautifulsoup4==4.12.3
+bibtexparser==2.0.0b7
+binaryornot==0.4.4
+bitsandbytes==0.42.0
+black==24.3.0
+blinker==1.7.0
+cached-property==1.5.2
+cachetools==5.3.3
+certifi==2024.2.2
+cffi==1.16.0
+chardet==5.2.0
+charset-normalizer==3.3.2
+chex==0.1.7
+click==8.1.7
+clldutils==3.22.2
+cmake==3.28.3
+codecarbon==1.2.0
+colorama==0.4.6
+coloredlogs==15.0.1
+colorlog==6.8.2
+comm==0.2.2
+cookiecutter==1.7.3
+csvw==3.3.0
+dash-bootstrap-components==1.5.0
+dash-core-components==2.0.0
+dash-html-components==2.0.0
+dash-table==5.0.0
+dash==2.16.1
+datasets==2.18.0
+debugpy==1.8.1
+decorator==5.1.1
+decord==0.6.0
+dill==0.3.4
+dlinfo==1.2.1
+dm-tree==0.1.8
+docker-pycreds==0.4.0
+einops==0.7.0
+etils==1.3.0
+evaluate==0.4.1
+exceptiongroup==1.2.0
+execnet==2.0.2
+executing==2.0.1
+faiss-cpu==1.8.0
+fastjsonschema==2.19.1
+filelock==3.13.1
+fire==0.6.0
+flatbuffers==24.3.7
+flax==0.7.0
+frozenlist==1.4.1
+fsspec==2024.3.0
+fugashi==1.3.1
+gast==0.4.0
+gitdb==4.0.11
+google-auth-oauthlib==1.0.0
+google-auth==2.28.2
+google-pasta==0.2.0
+greenlet==3.0.3
+grpcio==1.62.1
+h5py==3.11.0
+hf-doc-builder==0.5.0
+huggingface-hub==0.21.4
+humanfriendly==10.0
+hypothesis==6.99.8
+idna==3.6
+importlib_metadata==7.0.2
+importlib_resources==6.3.1
+iniconfig==2.0.0
+ipadic==1.0.0
+ipykernel==6.29.4
+ipython==8.12.3
+isodate==0.6.1
+isort==5.13.2
+itsdangerous==2.1.2
+jax==0.4.13
+jaxlib==0.4.13
+jedi==0.19.1
+jinja2-time==0.2.0
+joblib==1.3.2
+jsonschema-specifications==2023.12.1
+jsonschema==4.21.1
+jupyter_client==8.6.1
+jupyter_core==5.7.2
+kenlm==0.2.0
+keras-core==0.1.5
+keras-nlp==0.6.1
+keras==2.13.1
+language-tags==1.2.0
+lazy_loader==0.3
+libclang==18.1.1
+librosa==0.10.1
+lightning-utilities==0.11.2
+lightning==2.2.3
+lit==18.1.1
+llvmlite==0.41.1
+lxml==5.1.0
+markdown-it-py==3.0.0
+matplotlib-inline==0.1.7
+mdurl==0.1.2
+ml-dtypes==0.2.0
+mpmath==1.3.0
+msgpack==1.0.8
+multidict==6.0.5
+multiprocess==0.70.16
+mypy-extensions==1.0.0
+namex==0.0.8
+nbformat==5.10.3
+nest-asyncio==1.6.0
+networkx==3.1
+nltk==3.8.1
+numba==0.58.1
+numpy==1.24.4
+nvidia-cublas-cu11==11.10.3.66
+nvidia-cublas-cu12==12.1.3.1
+nvidia-cuda-cupti-cu11==11.7.101
+nvidia-cuda-cupti-cu12==12.1.105
+nvidia-cuda-nvrtc-cu11==11.7.99
+nvidia-cuda-nvrtc-cu12==12.1.105
+nvidia-cuda-runtime-cu11==11.7.99
+nvidia-cuda-runtime-cu12==12.1.105
+nvidia-cudnn-cu11==8.5.0.96
+nvidia-cudnn-cu12==8.9.2.26
+nvidia-cufft-cu11==10.9.0.58
+nvidia-cufft-cu12==11.0.2.54
+nvidia-curand-cu11==10.2.10.91
+nvidia-curand-cu12==10.3.2.106
+nvidia-cusolver-cu11==11.4.0.1
+nvidia-cusolver-cu12==11.4.5.107
+nvidia-cusparse-cu11==11.7.4.91
+nvidia-cusparse-cu12==12.1.0.106
+nvidia-nccl-cu11==2.14.3
+nvidia-nccl-cu12==2.20.5
+nvidia-nvjitlink-cu12==12.4.99
+nvidia-nvtx-cu11==11.7.91
+nvidia-nvtx-cu12==12.1.105
+oauthlib==3.2.2
+onnx==1.15.0
+onnxconverter-common==1.14.0
+onnxruntime-tools==1.7.0
+onnxruntime==1.16.3
+opt-einsum==3.3.0
+optax==0.1.4
+optuna==3.6.0
+orbax-checkpoint==0.2.3
+packaging==24.0
+pandas==2.0.3
+parameterized==0.9.0
+parso==0.8.4
+pathspec==0.12.1
+peft==0.10.0
+pexpect==4.9.0
+phonemizer==3.2.1
+pickleshare==0.7.5
+pillow==10.2.0
+pip==20.0.2
+pkg_resources==0.0.0
+pkgutil_resolve_name==1.3.10
+plac==1.4.3
+platformdirs==4.2.0
+plotly==5.20.0
+pluggy==1.4.0
+pooch==1.8.1
+portalocker==2.0.0
+poyo==0.5.0
+prompt-toolkit==3.0.43
+protobuf==4.25.3
+psutil==5.9.8
+ptyprocess==0.7.0
+pure-eval==0.2.2
+py-cpuinfo==9.0.0
+py3nvml==0.2.7
+pyarrow-hotfix==0.6
+pyarrow==15.0.1
+pyasn1-modules==0.3.0
+pyasn1==0.5.1
+pycparser==2.21
+pyctcdecode==0.5.0
+pydantic==2.6.4
+pydantic_core==2.16.3
+pygtrie==2.5.0
+pylatexenc==2.10
+pynvml==11.5.0
+pyparsing==3.1.2
+pypng==0.20220715.0
+pytest-timeout==2.3.1
+pytest-xdist==3.5.0
+pytest==7.4.4
+python-dateutil==2.9.0.post0
+python-slugify==8.0.4
+pytorch-lightning==2.2.3
+pytz==2024.1
+pyzmq==26.0.2
+rapidfuzz==3.8.1
+ray==2.9.3
+rdflib==7.0.0
+referencing==0.34.0
+regex==2023.12.25
+requests-oauthlib==1.4.0
+requests==2.31.0
+responses==0.18.0
+retrying==1.3.4
+rfc3986==1.5.0
+rhoknp==1.3.0
+rich==13.7.1
+rjieba==0.1.11
+rouge-score==0.1.2
+rpds-py==0.18.0
+rsa==4.9
+ruff==0.1.5
+sacrebleu==1.5.1
+sacremoses==0.1.1
+safetensors==0.4.2
+scikit-learn==1.3.2
+scipy==1.10.1
+segments==2.2.1
+sentencepiece==0.1.99
+sentry-sdk==2.0.1
+setproctitle==1.3.3
+setuptools==44.0.0
+sigopt==8.8.2
+six==1.16.0
+smmap==5.0.1
+sortedcontainers==2.4.0
+soundfile==0.12.1
+soupsieve==2.5
+soxr==0.3.7
+stack-data==0.6.3
+sympy==1.12
+tabulate==0.9.0
+tenacity==8.2.3
+tensorboard-data-server==0.7.2
+tensorboard==2.14.0
+tensorboardX==2.6.2.2
+tensorflow-estimator==2.13.0
+tensorflow-hub==0.16.1
+tensorflow-io-gcs-filesystem==0.34.0
+tensorflow-text==2.13.0
+tensorflow==2.13.1
+tensorstore==0.1.45
+termcolor==2.4.0
+text-unidecode==1.3
+tf2onnx==1.16.1
+tf_keras==2.15.1
+threadpoolctl==3.3.0
+timeout-decorator==0.5.0
+timm==0.9.16
+tokenizers==0.19.1
+tomli==2.0.1
+toolz==0.12.1
+torch==2.3.0
+torchaudio==2.1.2
+torchmetrics==1.3.2
+torchvision==0.18.0
+tornado==6.4
+tqdm==4.66.2
+traitlets==5.14.2
+transformers==4.41.0.dev0
+triton==2.3.0
+types-python-dateutil==2.9.0.20240316
+typing_extensions==4.10.0
+tzdata==2024.1
+tzlocal==5.2
+unidic-lite==1.0.8
+unidic==1.1.0
+uritemplate==4.1.1
+urllib3==1.26.18
+wandb==0.16.6
+wasabi==0.10.1
+wcwidth==0.2.13
+wheel==0.43.0
+wrapt==1.16.0
+xformers==0.0.22.post7
+xmltodict==0.13.0
+xxhash==3.4.1
+yarl==1.9.4
+zipp==3.18.1
\ No newline at end of file
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/wandb-metadata.json b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/wandb-metadata.json
new file mode 100644
index 00000000000000..becaf07f3ee16c
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/wandb-metadata.json
@@ -0,0 +1,703 @@
+{
+    "os": "Linux-5.4.0-166-generic-x86_64-with-glibc2.29",
+    "python": "3.8.10",
+    "heartbeatAt": "2024-04-30T10:40:41.318015",
+    "startedAt": "2024-04-30T10:40:40.643154",
+    "docker": null,
+    "cuda": null,
+    "args": [],
+    "state": "running",
+    "program": "<python with no main file>",
+    "codePathLocal": null,
+    "git": {
+        "remote": "git@github.com:NielsRogge/transformers.git",
+        "commit": "20a1cfa3db5bb5d96725d619a293500a81de0bc6"
+    },
+    "email": "niels.rogge1@gmail.com",
+    "root": "/home/niels/python_projects/transformers",
+    "host": "hf-dgx-01",
+    "username": "niels",
+    "executable": "/home/niels/python_projects/transformers/env/bin/python",
+    "cpu_count": 64,
+    "cpu_count_logical": 128,
+    "cpu_freq": {
+        "current": 2330.1935546875,
+        "min": 1500.0,
+        "max": 2250.0
+    },
+    "cpu_freq_per_core": [
+        {
+            "current": 3248.85,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1924.257,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1629.468,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.62,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3274.28,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.533,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.18,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.321,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.904,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3249.889,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1708.02,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.981,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.376,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.985,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3248.543,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3265.69,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3252.183,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.691,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1628.627,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.867,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3249.246,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.647,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1941.286,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.409,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1896.11,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3268.393,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.806,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2371.076,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3251.734,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.484,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.126,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.685,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1727.381,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2830.271,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1724.947,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1727.167,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3269.844,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1644.068,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2753.869,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1879.467,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3257.789,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1682.423,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2615.127,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1945.778,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.652,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2389.953,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3292.077,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.961,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3248.955,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3268.35,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3274.615,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.603,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3282.733,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.717,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3248.365,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3248.873,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3254.632,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1630.768,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1635.285,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.22,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3258.564,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.295,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.154,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.584,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3246.807,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1735.124,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1630.531,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.712,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3258.726,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.182,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.696,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.25,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.698,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3269.765,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.8,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.917,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.78,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1634.442,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2082.525,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3247.42,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3266.862,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.968,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2649.266,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1622.986,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3278.679,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1629.874,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3268.616,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1633.309,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2159.964,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3251.674,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1630.454,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1649.097,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3272.428,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1645.107,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1631.531,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1629.763,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2025.869,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2278.369,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1720.438,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1726.798,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3248.801,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1632.929,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3260.68,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2990.887,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2832.635,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1704.089,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2693.407,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2088.429,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1597.782,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2902.498,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3248.374,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1697.111,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3028.075,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1852.767,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1832.301,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3235.716,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3285.426,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 2197.554,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3245.66,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3282.193,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3279.416,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1639.283,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1638.016,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1638.133,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 3246.508,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1636.997,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1623.936,
+            "min": 1500.0,
+            "max": 2250.0
+        },
+        {
+            "current": 1639.282,
+            "min": 1500.0,
+            "max": 2250.0
+        }
+    ],
+    "disk": {
+        "/": {
+            "total": 1757.8785285949707,
+            "used": 1640.9605255126953
+        }
+    },
+    "gpu": "NVIDIA A100-SXM4-80GB",
+    "gpu_count": 5,
+    "gpu_devices": [
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        },
+        {
+            "name": "NVIDIA DGX Display",
+            "memory_total": 4294967296
+        },
+        {
+            "name": "NVIDIA A100-SXM4-80GB",
+            "memory_total": 85899345920
+        }
+    ],
+    "memory": {
+        "total": 503.5396919250488
+    }
+}
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/wandb-summary.json b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/wandb-summary.json
new file mode 100644
index 00000000000000..badd13293b538a
--- /dev/null
+++ b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/files/wandb-summary.json
@@ -0,0 +1 @@
+{"train_loss": 0.04636861011385918, "epoch": 0, "trainer/global_step": 49, "_timestamp": 1714473681.9160814, "_runtime": 41.268248319625854, "_step": 0}
\ No newline at end of file
diff --git a/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/run-t3hdwi09.wandb b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/run-t3hdwi09.wandb
new file mode 100644
index 00000000000000..6f9d7a44ea13a6
Binary files /dev/null and b/src/transformers/models/idefics2/wandb/run-20240430_124040-t3hdwi09/run-t3hdwi09.wandb differ
diff --git a/src/transformers/trainer_seq2seq.py b/src/transformers/trainer_seq2seq.py
index b6bce1b57d5e2a..20f6a6e4740762 100644
--- a/src/transformers/trainer_seq2seq.py
+++ b/src/transformers/trainer_seq2seq.py
@@ -307,6 +307,12 @@ def prediction_step(
             generation_inputs = {
                 k: v for k, v in inputs.items() if k not in ("decoder_input_ids", "decoder_attention_mask")
             }
+
+        print("Generation inputs:")
+        for k, v in generation_inputs.items():
+            if isinstance(v, torch.Tensor):
+                print(k, v.shape)
+
         generated_tokens = self.model.generate(**generation_inputs, **gen_kwargs)
 
         # Temporary hack to ensure the generation config is not initialized for each iteration of the evaluation loop