add ipynb to ipex example

examples/ipex/text-generation/ipex_text-generation.ipynb

@@ -0,0 +1,96 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# IPEX model for text-generation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "IPEX model will replace the linears and some ops. Please note that IPEXModel uses a graph mode model to inference to accelerate the generation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "from transformers import AutoTokenizer\n",
+    "from optimum.intel.ipex import IPEXModelForCausalLM"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Framework not specified. Using pt to export the model.\n",
+      "Passing the argument `library_name` to `get_supported_tasks_for_model_type` is required, but got library_name=None. Defaulting to `transformers`. An error will be raised in a future version of Optimum if `library_name` is not provided.\n",
+      "/home/jiqingfe/frameworks.ai.pytorch.ipex-cpu/intel_extension_for_pytorch/frontend.py:462: UserWarning: Conv BatchNorm folding failed during the optimize process.\n",
+      "  warnings.warn(\n",
+      "/home/jiqingfe/frameworks.ai.pytorch.ipex-cpu/intel_extension_for_pytorch/frontend.py:469: UserWarning: Linear BatchNorm folding failed during the optimize process.\n",
+      "  warnings.warn(\n",
+      "/home/jiqingfe/miniconda3/envs/ipex/lib/python3.10/site-packages/transformers/modeling_utils.py:4193: FutureWarning: `_is_quantized_training_enabled` is going to be deprecated in transformers 4.39.0. Please use `model.hf_quantizer.is_trainable` instead\n",
+      "  warnings.warn(\n",
+      "/home/jiqingfe/miniconda3/envs/ipex/lib/python3.10/site-packages/transformers/models/gpt2/modeling_gpt2.py:801: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!\n",
+      "  if batch_size <= 0:\n",
+      "Passing the argument `library_name` to `get_supported_tasks_for_model_type` is required, but got library_name=None. Defaulting to `transformers`. An error will be raised in a future version of Optimum if `library_name` is not provided.\n",
+      "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n",
+      "access to the `model_dtype` attribute is deprecated and will be removed after v1.18.0, please use `_dtype` instead.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Answer the following yes/no question by reasoning step-by-step please. Can you write a whole Haiku in a single tweet? Yes, you can.\n",
+      "\n",
+      "Yes, I can write Haikus in one tweet. I have no idea how to do that, but I'm sure\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = IPEXModelForCausalLM.from_pretrained(\"gpt2\", torch_dtype=torch.bfloat16, export=True)\n",
+    "tokenizer = AutoTokenizer.from_pretrained(\"gpt2\")\n",
+    "input_sentence = [\"Answer the following yes/no question by reasoning step-by-step please. Can you write a whole Haiku in a single tweet?\"]\n",
+    "model_inputs = tokenizer(input_sentence, return_tensors=\"pt\")\n",
+    "generation_kwargs = dict(max_new_tokens=32, do_sample=False, num_beams=4, num_beam_groups=1, no_repeat_ngram_size=2, use_cache=True)\n",
+    "\n",
+    "generated_ids = model.generate(**model_inputs, **generation_kwargs)\n",
+    "output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]\n",
+    "print(output)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "ipex",
+   "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": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}