consume_chroma.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import necessary libraries.\n",
    "from langchain.embeddings import HuggingFaceEmbeddings\n",
    "from langchain.vectorstores import Chroma\n",
    "from huggingface_hub import hf_hub_download\n",
    "from langchain.llms import LlamaCpp\n",
    "from langchain.callbacks.manager import CallbackManager\n",
    "from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
    "from langchain.chains.question_answering import load_qa_chain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define to variables to use \"sentence-transformers/all-MiniLM-L6-v2\" embedding model from HuggingFace.\n",
    "# https://huggingface.co/blog/getting-started-with-embeddings\n",
    "# https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2\n",
    "embeddings=HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the Chroma vector store and function to generate embeddings.\n",
    "db = Chroma(persist_directory=\"./chroma_db/\", embedding_function=embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "58 Building a superhero team - Get your teammates to read this\n",
      "\n",
      "Congratulations on finishing this book!\n",
      "\n",
      "In Chapter 2, we talked about how this book can help you become the superhero of your team.\n",
      "\n",
      "The only thing better than being a superhero is being part of a superhero team. I hope you’ll give copies of this book to your friends and teammates and help create other superheroes!\n",
      "\n",
      "Page 118\n",
      "\n",
      "Machine Learning Yearning-Draft\n",
      "\n",
      "Andrew Ng\n"
     ]
    }
   ],
   "source": [
    "# Define the query to search and display the most relevant document content.\n",
    "inquiry = \"Who is the author of this book?\"\n",
    "docs = db.similarity_search(inquiry)\n",
    "print(docs[0].page_content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "To disable this warning, you can either:\n",
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      "  [3/11] /Library/Developer/CommandLineTools/usr/bin/cc -DGGML_USE_ACCELERATE -DGGML_USE_K_QUANTS -DGGML_USE_METAL -D_DARWIN_C_SOURCE -D_XOPEN_SOURCE=600 -I/private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/. -F/Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk/System/Library/Frameworks -O3 -DNDEBUG -std=gnu11 -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk -fPIC -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -Wmissing-prototypes -Werror=implicit-int -Wno-unused-function -MD -MT vendor/llama.cpp/CMakeFiles/ggml.dir/ggml-metal.m.o -MF vendor/llama.cpp/CMakeFiles/ggml.dir/ggml-metal.m.o.d -o vendor/llama.cpp/CMakeFiles/ggml.dir/ggml-metal.m.o -c /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/ggml-metal.m\n",
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      "  [5/11] /Library/Developer/CommandLineTools/usr/bin/c++ -DGGML_USE_ACCELERATE -DGGML_USE_K_QUANTS -DGGML_USE_METAL -D_DARWIN_C_SOURCE -D_XOPEN_SOURCE=600 -I/private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/common/. -I/private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/. -O3 -DNDEBUG -std=gnu++11 -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk -fPIC -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -MD -MT vendor/llama.cpp/common/CMakeFiles/common.dir/grammar-parser.cpp.o -MF vendor/llama.cpp/common/CMakeFiles/common.dir/grammar-parser.cpp.o.d -o vendor/llama.cpp/common/CMakeFiles/common.dir/grammar-parser.cpp.o -c /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/common/grammar-parser.cpp\n",
      "  [6/11] /Library/Developer/CommandLineTools/usr/bin/c++ -DGGML_USE_ACCELERATE -DGGML_USE_K_QUANTS -DGGML_USE_METAL -D_DARWIN_C_SOURCE -D_XOPEN_SOURCE=600 -I/private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/common/. -I/private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/. -O3 -DNDEBUG -std=gnu++11 -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk -fPIC -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -MD -MT vendor/llama.cpp/common/CMakeFiles/common.dir/common.cpp.o -MF vendor/llama.cpp/common/CMakeFiles/common.dir/common.cpp.o.d -o vendor/llama.cpp/common/CMakeFiles/common.dir/common.cpp.o -c /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/common/common.cpp\n",
      "  [7/11] /Library/Developer/CommandLineTools/usr/bin/cc -DGGML_USE_ACCELERATE -DGGML_USE_K_QUANTS -DGGML_USE_METAL -D_DARWIN_C_SOURCE -D_XOPEN_SOURCE=600 -I/private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/. -F/Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk/System/Library/Frameworks -O3 -DNDEBUG -std=gnu11 -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk -fPIC -Wall -Wextra -Wpedantic -Wcast-qual -Wdouble-promotion -Wshadow -Wstrict-prototypes -Wpointer-arith -Wmissing-prototypes -Werror=implicit-int -Wno-unused-function -MD -MT vendor/llama.cpp/CMakeFiles/ggml.dir/ggml.c.o -MF vendor/llama.cpp/CMakeFiles/ggml.dir/ggml.c.o.d -o vendor/llama.cpp/CMakeFiles/ggml.dir/ggml.c.o -c /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/ggml.c\n",
      "  [8/11] : && /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-build-env-jv_74lb1/normal/lib/python3.11/site-packages/cmake/data/bin/cmake -E rm -f vendor/llama.cpp/libggml_static.a && /Library/Developer/CommandLineTools/usr/bin/ar qc vendor/llama.cpp/libggml_static.a  vendor/llama.cpp/CMakeFiles/ggml.dir/ggml.c.o vendor/llama.cpp/CMakeFiles/ggml.dir/ggml-alloc.c.o vendor/llama.cpp/CMakeFiles/ggml.dir/ggml-metal.m.o vendor/llama.cpp/CMakeFiles/ggml.dir/k_quants.c.o && /Library/Developer/CommandLineTools/usr/bin/ranlib vendor/llama.cpp/libggml_static.a && /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-build-env-jv_74lb1/normal/lib/python3.11/site-packages/cmake/data/bin/cmake -E touch vendor/llama.cpp/libggml_static.a && :\n",
      "  [9/11] : && /Library/Developer/CommandLineTools/usr/bin/cc -O3 -DNDEBUG -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk -dynamiclib -Wl,-headerpad_max_install_names  -o vendor/llama.cpp/libggml_shared.dylib -install_name @rpath/libggml_shared.dylib vendor/llama.cpp/CMakeFiles/ggml.dir/ggml.c.o vendor/llama.cpp/CMakeFiles/ggml.dir/ggml-alloc.c.o vendor/llama.cpp/CMakeFiles/ggml.dir/ggml-metal.m.o vendor/llama.cpp/CMakeFiles/ggml.dir/k_quants.c.o  -Xlinker -framework -Xlinker Accelerate  -Xlinker -framework -Xlinker Foundation  -Xlinker -framework -Xlinker Metal  -Xlinker -framework -Xlinker MetalKit && :\n",
      "  [10/11] /Library/Developer/CommandLineTools/usr/bin/c++ -DGGML_USE_ACCELERATE -DGGML_USE_K_QUANTS -DGGML_USE_METAL -DLLAMA_BUILD -DLLAMA_SHARED -D_DARWIN_C_SOURCE -D_XOPEN_SOURCE=600 -Dllama_EXPORTS -I/private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/. -F/Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk/System/Library/Frameworks -O3 -DNDEBUG -std=gnu++11 -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk -fPIC -Wall -Wextra -Wpedantic -Wcast-qual -Wno-unused-function -Wno-multichar -MD -MT vendor/llama.cpp/CMakeFiles/llama.dir/llama.cpp.o -MF vendor/llama.cpp/CMakeFiles/llama.dir/llama.cpp.o.d -o vendor/llama.cpp/CMakeFiles/llama.dir/llama.cpp.o -c /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/vendor/llama.cpp/llama.cpp\n",
      "  [11/11] : && /Library/Developer/CommandLineTools/usr/bin/c++ -O3 -DNDEBUG -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX13.3.sdk -dynamiclib -Wl,-headerpad_max_install_names  -o vendor/llama.cpp/libllama.dylib -install_name @rpath/libllama.dylib vendor/llama.cpp/CMakeFiles/ggml.dir/ggml.c.o vendor/llama.cpp/CMakeFiles/ggml.dir/ggml-alloc.c.o vendor/llama.cpp/CMakeFiles/ggml.dir/ggml-metal.m.o vendor/llama.cpp/CMakeFiles/ggml.dir/k_quants.c.o vendor/llama.cpp/CMakeFiles/llama.dir/llama.cpp.o  -Xlinker -framework -Xlinker Accelerate  -Xlinker -framework -Xlinker Foundation  -Xlinker -framework -Xlinker Metal  -Xlinker -framework -Xlinker MetalKit && :\n",
      "\n",
      "  \u001b[92m***\u001b[0m \u001b[1mInstalling project into wheel...\u001b[0m\n",
      "  -- Install configuration: \"Release\"\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/lib/libggml_shared.dylib\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/lib/cmake/Llama/LlamaConfig.cmake\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/lib/cmake/Llama/LlamaConfigVersion.cmake\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/include/ggml.h\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/include/ggml-metal.h\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/include/k_quants.h\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/lib/libllama.dylib\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/include/llama.h\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/bin/convert.py\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/bin/convert-lora-to-ggml.py\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/bin/ggml-metal.metal\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/llama_cpp/libllama.dylib\n",
      "  -- Installing: /var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/tmpvoecc5t0/wheel/platlib/llama_cpp/ggml-metal.metal\n",
      "  -- Installing: /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/llama_cpp/libllama.dylib\n",
      "  -- Installing: /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-install-w7dz1b2u/llama-cpp-python_d21770cd3aa547568838753815cea261/llama_cpp/ggml-metal.metal\n",
      "  \u001b[92m***\u001b[0m \u001b[1mMaking wheel...\u001b[0m\n",
      "  \u001b[92m***\u001b[0m \u001b[1mCreated\u001b[22m llama_cpp_python-0.2.6-cp311-cp311-macosx_13_0_arm64.whl...\u001b[0m\n",
      "\u001b[?25hdone\n",
      "  Created wheel for llama-cpp-python: filename=llama_cpp_python-0.2.6-cp311-cp311-macosx_13_0_arm64.whl size=851311 sha256=587bf81f89a9cf2d49dd2b9deb634a2dc7cffc5e9bb27a14b3da3e2f77af0605\n",
      "  Stored in directory: /private/var/folders/s5/d5_419x12qnbmsszkklmtwb40000gn/T/pip-ephem-wheel-cache-wxqj5t6k/wheels/18/f3/e6/e6d374c76db44b5b0451c3a76b3049f29e881819bc43f53d4d\n",
      "Successfully built llama-cpp-python\n",
      "Installing collected packages: typing-extensions, numpy, diskcache, llama-cpp-python\n",
      "  Attempting uninstall: typing-extensions\n",
      "    Found existing installation: typing_extensions 4.7.1\n",
      "    Uninstalling typing_extensions-4.7.1:\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/__pycache__/typing_extensions.cpython-311.pyc\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/typing_extensions-4.7.1.dist-info/\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/typing_extensions.py\n",
      "      Successfully uninstalled typing_extensions-4.7.1\n",
      "  Attempting uninstall: numpy\n",
      "    Found existing installation: numpy 1.25.2\n",
      "    Uninstalling numpy-1.25.2:\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/bin/f2py\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/bin/f2py3\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/bin/f2py3.11\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/numpy-1.25.2.dist-info/\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/numpy/\n",
      "      Successfully uninstalled numpy-1.25.2\n",
      "  changing mode of /Users/easonlai/anaconda3/envs/llama2/bin/f2py to 755\n",
      "  changing mode of /Users/easonlai/anaconda3/envs/llama2/bin/f2py3 to 755\n",
      "  changing mode of /Users/easonlai/anaconda3/envs/llama2/bin/f2py3.11 to 755\n",
      "  Attempting uninstall: diskcache\n",
      "    Found existing installation: diskcache 5.6.3\n",
      "    Uninstalling diskcache-5.6.3:\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/diskcache-5.6.3.dist-info/\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/diskcache/\n",
      "      Successfully uninstalled diskcache-5.6.3\n",
      "  Attempting uninstall: llama-cpp-python\n",
      "    Found existing installation: llama_cpp_python 0.2.6\n",
      "    Uninstalling llama_cpp_python-0.2.6:\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/bin/\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/include/\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/lib/\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/llama_cpp/\n",
      "      Removing file or directory /Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/llama_cpp_python-0.2.6.dist-info/\n",
      "      Successfully uninstalled llama_cpp_python-0.2.6\n",
      "Successfully installed diskcache-5.6.3 llama-cpp-python-0.2.6 numpy-1.25.2 typing-extensions-4.7.1\n"
     ]
    }
   ],
   "source": [
    "# Install llama-cpp-python library to use llama.cpp.\n",
    "# https://python.langchain.com/docs/integrations/llms/llamacpp\n",
    "# !CMAKE_ARGS=\"-DLLAMA_CUBLAS=on\" FORCE_CMAKE=1 pip install llama-cpp-python --force-reinstall --upgrade --no-cache-dir --verbose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Defien the Llama 2 model name, path, and base name to use.\n",
    "# https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML\n",
    "model_name_or_path = \"TheBloke/Llama-2-13B-chat-GGUF\"\n",
    "model_basename = \"llama-2-13b-chat.Q4_K_M.gguf\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Construst the model path and download the model from HuggingFace.\n",
    "model_path = hf_hub_download(repo_id=model_name_or_path, filename=model_basename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/easonlai/.cache/huggingface/hub/models--TheBloke--Llama-2-13B-chat-GGUF/snapshots/245bc5104d85dcc9a11a0e0a9ae6de38dfae536f/llama-2-13b-chat.Q4_K_M.gguf\n"
     ]
    }
   ],
   "source": [
    "# Print out the model path.\n",
    "print(model_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Callbacks support token-wise streaming.\n",
    "callback_manager = CallbackManager([StreamingStdOutCallbackHandler()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "llama_model_loader: loaded meta data with 19 key-value pairs and 363 tensors from /Users/easonlai/.cache/huggingface/hub/models--TheBloke--Llama-2-13B-chat-GGUF/snapshots/245bc5104d85dcc9a11a0e0a9ae6de38dfae536f/llama-2-13b-chat.Q4_K_M.gguf (version GGUF V2 (latest))\n",
      "llama_model_loader: - tensor    0:                token_embd.weight q4_K     [  5120, 32000,     1,     1 ]\n",
      "llama_model_loader: - tensor    1:           blk.0.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor    2:            blk.0.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor    3:            blk.0.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor    4:              blk.0.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor    5:            blk.0.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor    6:              blk.0.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor    7:         blk.0.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor    8:              blk.0.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor    9:              blk.0.attn_v.weight q6_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   10:           blk.1.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   11:            blk.1.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   12:            blk.1.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   13:              blk.1.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   14:            blk.1.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   15:              blk.1.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   16:         blk.1.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   17:              blk.1.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   18:              blk.1.attn_v.weight q6_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   19:          blk.10.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   20:           blk.10.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   21:           blk.10.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   22:             blk.10.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   23:           blk.10.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   24:             blk.10.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   25:        blk.10.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   26:             blk.10.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   27:             blk.10.attn_v.weight q6_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   28:          blk.11.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   29:           blk.11.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   30:           blk.11.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   31:             blk.11.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   32:           blk.11.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   33:             blk.11.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   34:        blk.11.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   35:             blk.11.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
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      "llama_model_loader: - tensor   37:          blk.12.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   38:           blk.12.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   39:           blk.12.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   40:             blk.12.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   41:           blk.12.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   42:             blk.12.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   43:        blk.12.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   44:             blk.12.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   45:             blk.12.attn_v.weight q6_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   46:          blk.13.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   47:           blk.13.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   48:           blk.13.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   49:             blk.13.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   50:           blk.13.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   51:             blk.13.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   52:        blk.13.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   53:             blk.13.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   54:             blk.13.attn_v.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   55:          blk.14.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   56:           blk.14.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   57:           blk.14.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   58:             blk.14.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   59:           blk.14.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   60:             blk.14.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   61:        blk.14.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   62:             blk.14.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   63:             blk.14.attn_v.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   64:             blk.15.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   65:             blk.15.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   66:           blk.2.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   67:            blk.2.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   68:            blk.2.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   69:              blk.2.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   70:            blk.2.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   71:              blk.2.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   72:         blk.2.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   73:              blk.2.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   74:              blk.2.attn_v.weight q6_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   75:           blk.3.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   76:            blk.3.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   77:            blk.3.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   78:              blk.3.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   79:            blk.3.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   80:              blk.3.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   81:         blk.3.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   82:              blk.3.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   83:              blk.3.attn_v.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   84:           blk.4.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   85:            blk.4.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   86:            blk.4.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   87:              blk.4.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   88:            blk.4.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
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      "llama_model_loader: - tensor   90:         blk.4.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
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      "llama_model_loader: - tensor   93:           blk.5.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   94:            blk.5.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor   95:            blk.5.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   96:              blk.5.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor   97:            blk.5.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor   98:              blk.5.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
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      "llama_model_loader: - tensor  102:           blk.6.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  103:            blk.6.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  104:            blk.6.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  105:              blk.6.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  106:            blk.6.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  107:              blk.6.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
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      "llama_model_loader: - tensor  109:              blk.6.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
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      "llama_model_loader: - tensor  111:           blk.7.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  112:            blk.7.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  113:            blk.7.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  114:              blk.7.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  115:            blk.7.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
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      "llama_model_loader: - tensor  120:           blk.8.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  121:            blk.8.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  122:            blk.8.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  123:              blk.8.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  124:            blk.8.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
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      "llama_model_loader: - tensor  129:           blk.9.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  130:            blk.9.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  131:            blk.9.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  132:              blk.9.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  133:            blk.9.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  134:              blk.9.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
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      "llama_model_loader: - tensor  136:              blk.9.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  137:              blk.9.attn_v.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  138:          blk.15.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  139:           blk.15.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  140:           blk.15.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  141:             blk.15.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  142:           blk.15.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  143:        blk.15.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  144:             blk.15.attn_v.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  145:          blk.16.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  146:           blk.16.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  147:           blk.16.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  148:             blk.16.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  149:           blk.16.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  150:             blk.16.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  151:        blk.16.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  152:             blk.16.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  153:             blk.16.attn_v.weight q6_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  154:          blk.17.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  155:           blk.17.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  156:           blk.17.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  157:             blk.17.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  158:           blk.17.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  159:             blk.17.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  160:        blk.17.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  161:             blk.17.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  162:             blk.17.attn_v.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  163:          blk.18.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  164:           blk.18.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  165:           blk.18.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  166:             blk.18.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  167:           blk.18.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  168:             blk.18.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  169:        blk.18.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  170:             blk.18.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  171:             blk.18.attn_v.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  172:          blk.19.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  173:           blk.19.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  174:           blk.19.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  175:             blk.19.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  176:           blk.19.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  177:             blk.19.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  178:        blk.19.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  179:             blk.19.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  180:             blk.19.attn_v.weight q6_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  181:          blk.20.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  182:           blk.20.ffn_down.weight q4_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  183:           blk.20.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  184:             blk.20.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
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      "llama_model_loader: - tensor  344:          blk.38.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
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      "llama_model_loader: - tensor  348:           blk.38.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  349:             blk.38.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  350:        blk.38.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  351:             blk.38.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  352:             blk.38.attn_v.weight q6_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  353:          blk.39.attn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  354:           blk.39.ffn_down.weight q6_K     [ 13824,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  355:           blk.39.ffn_gate.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  356:             blk.39.ffn_up.weight q4_K     [  5120, 13824,     1,     1 ]\n",
      "llama_model_loader: - tensor  357:           blk.39.ffn_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - tensor  358:             blk.39.attn_k.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  359:        blk.39.attn_output.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  360:             blk.39.attn_q.weight q4_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  361:             blk.39.attn_v.weight q6_K     [  5120,  5120,     1,     1 ]\n",
      "llama_model_loader: - tensor  362:               output_norm.weight f32      [  5120,     1,     1,     1 ]\n",
      "llama_model_loader: - kv   0:                       general.architecture str     \n",
      "llama_model_loader: - kv   1:                               general.name str     \n",
      "llama_model_loader: - kv   2:                       llama.context_length u32     \n",
      "llama_model_loader: - kv   3:                     llama.embedding_length u32     \n",
      "llama_model_loader: - kv   4:                          llama.block_count u32     \n",
      "llama_model_loader: - kv   5:                  llama.feed_forward_length u32     \n",
      "llama_model_loader: - kv   6:                 llama.rope.dimension_count u32     \n",
      "llama_model_loader: - kv   7:                 llama.attention.head_count u32     \n",
      "llama_model_loader: - kv   8:              llama.attention.head_count_kv u32     \n",
      "llama_model_loader: - kv   9:     llama.attention.layer_norm_rms_epsilon f32     \n",
      "llama_model_loader: - kv  10:                          general.file_type u32     \n",
      "llama_model_loader: - kv  11:                       tokenizer.ggml.model str     \n",
      "llama_model_loader: - kv  12:                      tokenizer.ggml.tokens arr     \n",
      "llama_model_loader: - kv  13:                      tokenizer.ggml.scores arr     \n",
      "llama_model_loader: - kv  14:                  tokenizer.ggml.token_type arr     \n",
      "llama_model_loader: - kv  15:                tokenizer.ggml.bos_token_id u32     \n",
      "llama_model_loader: - kv  16:                tokenizer.ggml.eos_token_id u32     \n",
      "llama_model_loader: - kv  17:            tokenizer.ggml.unknown_token_id u32     \n",
      "llama_model_loader: - kv  18:               general.quantization_version u32     \n",
      "llama_model_loader: - type  f32:   81 tensors\n",
      "llama_model_loader: - type q4_K:  241 tensors\n",
      "llama_model_loader: - type q6_K:   41 tensors\n",
      "llm_load_print_meta: format         = GGUF V2 (latest)\n",
      "llm_load_print_meta: arch           = llama\n",
      "llm_load_print_meta: vocab type     = SPM\n",
      "llm_load_print_meta: n_vocab        = 32000\n",
      "llm_load_print_meta: n_merges       = 0\n",
      "llm_load_print_meta: n_ctx_train    = 4096\n",
      "llm_load_print_meta: n_ctx          = 2048\n",
      "llm_load_print_meta: n_embd         = 5120\n",
      "llm_load_print_meta: n_head         = 40\n",
      "llm_load_print_meta: n_head_kv      = 40\n",
      "llm_load_print_meta: n_layer        = 40\n",
      "llm_load_print_meta: n_rot          = 128\n",
      "llm_load_print_meta: n_gqa          = 1\n",
      "llm_load_print_meta: f_norm_eps     = 1.0e-05\n",
      "llm_load_print_meta: f_norm_rms_eps = 1.0e-05\n",
      "llm_load_print_meta: n_ff           = 13824\n",
      "llm_load_print_meta: freq_base      = 10000.0\n",
      "llm_load_print_meta: freq_scale     = 1\n",
      "llm_load_print_meta: model type     = 13B\n",
      "llm_load_print_meta: model ftype    = mostly Q4_K - Medium\n",
      "llm_load_print_meta: model size     = 13.02 B\n",
      "llm_load_print_meta: general.name   = LLaMA v2\n",
      "llm_load_print_meta: BOS token = 1 '<s>'\n",
      "llm_load_print_meta: EOS token = 2 '</s>'\n",
      "llm_load_print_meta: UNK token = 0 '<unk>'\n",
      "llm_load_print_meta: LF token  = 13 '<0x0A>'\n",
      "llm_load_tensors: ggml ctx size =    0.12 MB\n",
      "llm_load_tensors: mem required  = 7500.97 MB (+ 1600.00 MB per state)\n",
      "....................................................................................................\n",
      "llama_new_context_with_model: kv self size  = 1600.00 MB\n",
      "ggml_metal_init: allocating\n",
      "ggml_metal_init: found device: Apple M2\n",
      "ggml_metal_init: picking default device: Apple M2\n",
      "ggml_metal_init: loading '/Users/easonlai/anaconda3/envs/llama2/lib/python3.11/site-packages/llama_cpp/ggml-metal.metal'\n",
      "ggml_metal_init: loaded kernel_add                            0x29c307050 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_add_row                        0x29c3072b0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul                            0x29c307510 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_row                        0x29c307770 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_scale                          0x29c3079d0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_silu                           0x29c307c30 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_relu                           0x29c307e90 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_gelu                           0x29c3080f0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_soft_max                       0x29c308350 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_soft_max_4                     0x29c3085b0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_diag_mask_inf                  0x29c308810 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_diag_mask_inf_8                0x29c308a70 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_f32                   0x29c308cd0 | th_max =  896 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_f16                   0x29c308f30 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_q4_0                  0x29c309190 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_q4_1                  0x29c3093f0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_q8_0                  0x29c309650 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_q2_K                  0x29c3098b0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_q3_K                  0x29c309b10 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_q4_K                  0x29c309d70 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_q5_K                  0x29c309fd0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_get_rows_q6_K                  0x29c30a230 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_rms_norm                       0x29c30a490 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_norm                           0x29c30a6f0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_f32_f32                0x29c30a950 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_f16_f32                0x29c30abb0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_f16_f32_1row           0x29c30ae10 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_f16_f32_l4             0x29c30b070 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_q4_0_f32               0x29c30b2d0 | th_max =  896 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_q4_1_f32               0x29c30b530 | th_max =  896 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_q8_0_f32               0x29c30b790 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_q2_K_f32               0x29c30b9f0 | th_max =  640 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_q3_K_f32               0x29c30bc50 | th_max =  576 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_q4_K_f32               0x29c30beb0 | th_max =  576 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_q5_K_f32               0x29c30c110 | th_max =  640 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mat_q6_K_f32               0x29c30c370 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_f32_f32                 0x29c30c5d0 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_f16_f32                 0x29c30c830 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_q4_0_f32                0x29c30ca90 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_q8_0_f32                0x29c30ccf0 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_q4_1_f32                0x29c30cf50 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_q2_K_f32                0x29c30d1b0 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_q3_K_f32                0x29c30d410 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_q4_K_f32                0x29c30d670 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_q5_K_f32                0x29c30d8d0 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_mul_mm_q6_K_f32                0x29c30db30 | th_max =  768 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_rope                           0x29c30dd90 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_alibi_f32                      0x29c30dff0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_cpy_f32_f16                    0x29c30e250 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_cpy_f32_f32                    0x29c30e4b0 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: loaded kernel_cpy_f16_f16                    0x29c30e710 | th_max = 1024 | th_width =   32\n",
      "ggml_metal_init: hasUnifiedMemory              = true\n",
      "ggml_metal_init: recommendedMaxWorkingSetSize  = 10922.67 MB\n",
      "ggml_metal_init: maxTransferRate               = built-in GPU\n",
      "llama_new_context_with_model: compute buffer total size =  211.47 MB\n",
      "llama_new_context_with_model: max tensor size =   128.17 MB\n",
      "ggml_metal_add_buffer: allocated 'data            ' buffer, size =  7501.56 MB, (15942.88 / 10922.67), warning: current allocated size is greater than the recommended max working set size\n",
      "ggml_metal_add_buffer: allocated 'eval            ' buffer, size =     1.48 MB, (15944.36 / 10922.67), warning: current allocated size is greater than the recommended max working set size\n",
      "ggml_metal_add_buffer: allocated 'kv              ' buffer, size =  1602.00 MB, (17546.36 / 10922.67), warning: current allocated size is greater than the recommended max working set size\n",
      "ggml_metal_add_buffer: allocated 'alloc           ' buffer, size =   210.02 MB, (17756.38 / 10922.67), warning: current allocated size is greater than the recommended max working set size\n"
     ]
    }
   ],
   "source": [
    "# Reference configuration for GPU https://python.langchain.com/docs/integrations/llms/llamacpp#gpu.\n",
    "n_gpu_layers = 40  # Change this value based on your model and your GPU VRAM pool.\n",
    "n_batch = 512  # Should be between 1 and n_ctx, consider the amount of VRAM in your GPU.\n",
    "\n",
    "# Initialize the llamaCpp model.\n",
    "llm = LlamaCpp(\n",
    "    model_path=model_path,\n",
    "    max_tokens=256,\n",
    "    n_gpu_layers=n_gpu_layers,\n",
    "    n_batch=n_batch,\n",
    "    callback_manager=callback_manager,\n",
    "    n_ctx=2048,\n",
    "    verbose=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ggml_metal_free: deallocating\n"
     ]
    }
   ],
   "source": [
    "# Initialize the question answering chain.\n",
    "chain = load_qa_chain(llm, chain_type=\"stuff\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The author of this book is Andrew Ng."
     ]
    },
    {
     "data": {
      "text/plain": [
       "' The author of this book is Andrew Ng.'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Perform first sample of question answering.\n",
    "inquiry = \"Who is the author of this book?\"\n",
    "docs = db.similarity_search(inquiry)\n",
    "chain.run(input_documents=docs, question=inquiry)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The book talks about how to build a superhero team and become the superhero of your team using machine learning yearning draft, written by Andrew Ng, to help you understand how to set technical direction for a machine learning project, persuade your teammates to follow it, and scale your team's progress."
     ]
    },
    {
     "data": {
      "text/plain": [
       "\" The book talks about how to build a superhero team and become the superhero of your team using machine learning yearning draft, written by Andrew Ng, to help you understand how to set technical direction for a machine learning project, persuade your teammates to follow it, and scale your team's progress.\""
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Perform second sample of question answering.\n",
    "inquiry = \"Please tell me the key summary of this book.\"\n",
    "docs = db.similarity_search(inquiry)\n",
    "chain.run(input_documents=docs, question=inquiry)"
   ]
  }
 ],
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