llama.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "executionInfo": {
     "elapsed": 128962,
     "status": "ok",
     "timestamp": 1718001635617,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "CLQkFSqdtoDv",
    "scrolled": true
   },
   "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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: accelerate in /home/oignat/.local/lib/python3.9/site-packages (0.31.0)\n",
      "Requirement already satisfied: huggingface-hub in /home/oignat/.local/lib/python3.9/site-packages (from accelerate) (0.23.3)\n",
      "Requirement already satisfied: psutil in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from accelerate) (5.8.0)\n",
      "Requirement already satisfied: packaging>=20.0 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from accelerate) (21.0)\n",
      "Requirement already satisfied: safetensors>=0.3.1 in /home/oignat/.local/lib/python3.9/site-packages (from accelerate) (0.4.3)\n",
      "Requirement already satisfied: pyyaml in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from accelerate) (6.0)\n",
      "Requirement already satisfied: numpy>=1.17 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from accelerate) (1.20.3)\n",
      "Requirement already satisfied: torch>=1.10.0 in /home/oignat/.local/lib/python3.9/site-packages (from accelerate) (2.3.1)\n",
      "Requirement already satisfied: pyparsing>=2.0.2 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from packaging>=20.0->accelerate) (3.0.4)\n",
      "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (12.1.3.1)\n",
      "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (11.4.5.107)\n",
      "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (12.1.0.106)\n",
      "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (8.9.2.26)\n",
      "Requirement already satisfied: typing-extensions>=4.8.0 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (4.12.2)\n",
      "Requirement already satisfied: networkx in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (2.6.3)\n",
      "Requirement already satisfied: filelock in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (3.3.1)\n",
      "Requirement already satisfied: triton==2.3.1 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (2.3.1)\n",
      "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (12.1.105)\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (12.1.105)\n",
      "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (10.3.2.106)\n",
      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (12.1.105)\n",
      "Requirement already satisfied: jinja2 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (3.1.2)\n",
      "Requirement already satisfied: fsspec in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (2024.3.1)\n",
      "Requirement already satisfied: nvidia-nccl-cu12==2.20.5 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (2.20.5)\n",
      "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (11.0.2.54)\n",
      "Requirement already satisfied: sympy in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (1.9)\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (12.1.105)\n",
      "Requirement already satisfied: nvidia-nvjitlink-cu12 in /home/oignat/.local/lib/python3.9/site-packages (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.10.0->accelerate) (12.5.40)\n",
      "Requirement already satisfied: requests in /home/oignat/.local/lib/python3.9/site-packages (from huggingface-hub->accelerate) (2.32.3)\n",
      "Requirement already satisfied: tqdm>=4.42.1 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from huggingface-hub->accelerate) (4.62.3)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.1)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from requests->huggingface-hub->accelerate) (1.26.7)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from requests->huggingface-hub->accelerate) (3.2)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from requests->huggingface-hub->accelerate) (2.0.4)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from requests->huggingface-hub->accelerate) (2021.10.8)\n",
      "Requirement already satisfied: mpmath>=0.19 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from sympy->torch>=1.10.0->accelerate) (1.2.1)\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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: peft in /home/oignat/.local/lib/python3.9/site-packages (0.11.1)\n",
      "Requirement already satisfied: safetensors in /home/oignat/.local/lib/python3.9/site-packages (from peft) (0.4.3)\n",
      "Requirement already satisfied: accelerate>=0.21.0 in /home/oignat/.local/lib/python3.9/site-packages (from peft) (0.31.0)\n",
      "Requirement already satisfied: tqdm in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from peft) (4.62.3)\n",
      "Requirement already satisfied: transformers in /home/oignat/.local/lib/python3.9/site-packages (from peft) (4.41.2)\n",
      "Requirement already satisfied: huggingface-hub>=0.17.0 in /home/oignat/.local/lib/python3.9/site-packages (from peft) (0.23.3)\n",
      "Requirement already satisfied: packaging>=20.0 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from peft) (21.0)\n",
      "Requirement already satisfied: pyyaml in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from peft) (6.0)\n",
      "Requirement already satisfied: torch>=1.13.0 in /home/oignat/.local/lib/python3.9/site-packages (from peft) (2.3.1)\n",
      "Requirement already satisfied: psutil in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from peft) (5.8.0)\n",
      "Requirement already satisfied: numpy>=1.17 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from peft) (1.20.3)\n",
      "Requirement already satisfied: requests in /home/oignat/.local/lib/python3.9/site-packages (from huggingface-hub>=0.17.0->peft) (2.32.3)\n",
      "Requirement already satisfied: fsspec>=2023.5.0 in /home/oignat/.local/lib/python3.9/site-packages (from huggingface-hub>=0.17.0->peft) (2024.3.1)\n",
      "Requirement already satisfied: filelock in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from huggingface-hub>=0.17.0->peft) (3.3.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /home/oignat/.local/lib/python3.9/site-packages (from huggingface-hub>=0.17.0->peft) (4.12.2)\n",
      "Requirement already satisfied: pyparsing>=2.0.2 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from packaging>=20.0->peft) (3.0.4)\n",
      "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (8.9.2.26)\n",
      "Requirement already satisfied: sympy in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch>=1.13.0->peft) (1.9)\n",
      "Requirement already satisfied: nvidia-nccl-cu12==2.20.5 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (2.20.5)\n",
      "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (12.1.105)\n",
      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (12.1.105)\n",
      "Requirement already satisfied: jinja2 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch>=1.13.0->peft) (3.1.2)\n",
      "Requirement already satisfied: networkx in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch>=1.13.0->peft) (2.6.3)\n",
      "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (11.4.5.107)\n",
      "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (11.0.2.54)\n",
      "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (12.1.0.106)\n",
      "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (10.3.2.106)\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (12.1.105)\n",
      "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (12.1.3.1)\n",
      "Requirement already satisfied: triton==2.3.1 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (2.3.1)\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch>=1.13.0->peft) (12.1.105)\n",
      "Requirement already satisfied: nvidia-nvjitlink-cu12 in /home/oignat/.local/lib/python3.9/site-packages (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.13.0->peft) (12.5.40)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from jinja2->torch>=1.13.0->peft) (2.1.1)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from requests->huggingface-hub>=0.17.0->peft) (2.0.4)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from requests->huggingface-hub>=0.17.0->peft) (2021.10.8)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from requests->huggingface-hub>=0.17.0->peft) (3.2)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from requests->huggingface-hub>=0.17.0->peft) (1.26.7)\n",
      "Requirement already satisfied: mpmath>=0.19 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from sympy->torch>=1.13.0->peft) (1.2.1)\n",
      "Requirement already satisfied: regex!=2019.12.17 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from transformers->peft) (2021.8.3)\n",
      "Requirement already satisfied: tokenizers<0.20,>=0.19 in /home/oignat/.local/lib/python3.9/site-packages (from transformers->peft) (0.19.1)\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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: bitsandbytes in /home/oignat/.local/lib/python3.9/site-packages (0.43.1)\n",
      "Requirement already satisfied: numpy in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from bitsandbytes) (1.20.3)\n",
      "Requirement already satisfied: torch in /home/oignat/.local/lib/python3.9/site-packages (from bitsandbytes) (2.3.1)\n",
      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (12.1.105)\n",
      "Requirement already satisfied: jinja2 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch->bitsandbytes) (3.1.2)\n",
      "Requirement already satisfied: typing-extensions>=4.8.0 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (4.12.2)\n",
      "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (11.0.2.54)\n",
      "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (12.1.0.106)\n",
      "Requirement already satisfied: sympy in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch->bitsandbytes) (1.9)\n",
      "Requirement already satisfied: networkx in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch->bitsandbytes) (2.6.3)\n",
      "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (11.4.5.107)\n",
      "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (8.9.2.26)\n",
      "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (10.3.2.106)\n",
      "Requirement already satisfied: nvidia-nccl-cu12==2.20.5 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (2.20.5)\n",
      "Requirement already satisfied: filelock in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from torch->bitsandbytes) (3.3.1)\n",
      "Requirement already satisfied: fsspec in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (2024.3.1)\n",
      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (12.1.105)\n",
      "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (12.1.105)\n",
      "Requirement already satisfied: triton==2.3.1 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (2.3.1)\n",
      "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (12.1.3.1)\n",
      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /home/oignat/.local/lib/python3.9/site-packages (from torch->bitsandbytes) (12.1.105)\n",
      "Requirement already satisfied: nvidia-nvjitlink-cu12 in /home/oignat/.local/lib/python3.9/site-packages (from nvidia-cusolver-cu12==11.4.5.107->torch->bitsandbytes) (12.5.40)\n",
      "Requirement already satisfied: MarkupSafe>=2.0 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from jinja2->torch->bitsandbytes) (2.1.1)\n",
      "Requirement already satisfied: mpmath>=0.19 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from sympy->torch->bitsandbytes) (1.2.1)\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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: transformers in /home/oignat/.local/lib/python3.9/site-packages (4.41.2)\n",
      "Requirement already satisfied: numpy>=1.17 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from transformers) (1.20.3)\n",
      "Requirement already satisfied: tqdm>=4.27 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from transformers) (4.62.3)\n",
      "Requirement already satisfied: pyyaml>=5.1 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from transformers) (6.0)\n",
      "Requirement already satisfied: filelock in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from transformers) (3.3.1)\n",
      "Requirement already satisfied: requests in /home/oignat/.local/lib/python3.9/site-packages (from transformers) (2.32.3)\n",
      "Requirement already satisfied: huggingface-hub<1.0,>=0.23.0 in /home/oignat/.local/lib/python3.9/site-packages (from transformers) (0.23.3)\n",
      "Requirement already satisfied: tokenizers<0.20,>=0.19 in /home/oignat/.local/lib/python3.9/site-packages (from transformers) (0.19.1)\n",
      "Requirement already satisfied: safetensors>=0.4.1 in /home/oignat/.local/lib/python3.9/site-packages (from transformers) (0.4.3)\n",
      "Requirement already satisfied: regex!=2019.12.17 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from transformers) (2021.8.3)\n",
      "Requirement already satisfied: packaging>=20.0 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from transformers) (21.0)\n",
      "Requirement already satisfied: fsspec>=2023.5.0 in /home/oignat/.local/lib/python3.9/site-packages (from huggingface-hub<1.0,>=0.23.0->transformers) (2024.3.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /home/oignat/.local/lib/python3.9/site-packages (from huggingface-hub<1.0,>=0.23.0->transformers) (4.12.2)\n",
      "Requirement already satisfied: pyparsing>=2.0.2 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from packaging>=20.0->transformers) (3.0.4)\n",
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     ]
    },
    {
     "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"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: python-dateutil>=2.7.3 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from pandas->datasets->trl) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2017.3 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from pandas->datasets->trl) (2021.3)\n",
      "Requirement already satisfied: six>=1.5 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from python-dateutil>=2.7.3->pandas->datasets->trl) (1.16.0)\n",
      "Requirement already satisfied: mpmath>=0.19 in /sw/pkgs/arc/python3.9-anaconda/2021.11/lib/python3.9/site-packages (from sympy->torch>=1.4.0->trl) (1.2.1)\n"
     ]
    }
   ],
   "source": [
    "# %%capture\n",
    "\n",
    "# # This command installs several Python packages that are necessary for fine-tuning and optimizing language models:\n",
    "!pip install accelerate       # A PyTorch extension for distributed training and performance optimization.\n",
    "!pip install peft             # PEFT (Parameter-efficient Fine-tuning): Techniques for efficient fine-tuning of models.\n",
    "!pip install bitsandbytes     # Library for efficient training of deep learning models, focusing on memory and speed optimization.\n",
    "!pip install transformers     # Provides thousands of pre-trained models to perform tasks on texts such as classification, information extraction, and more.\n",
    "!pip install trl              # Token-level Reinforcement Learning for training language models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/sw/pkgs/arc/python3.9-anaconda/2021.11/bin/python\r\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": [
    "!which python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "executionInfo": {
     "elapsed": 17092,
     "status": "ok",
     "timestamp": 1718001652703,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "dSiVW72gna6_"
   },
   "outputs": [],
   "source": [
    "# Importing essential modules and functions from various libraries:\n",
    "import os                        # os module: Provides a way of using operating system dependent functionality.\n",
    "import torch                     # PyTorch: A deep learning framework for tensor computation and automatic differentiation.\n",
    "\n",
    "# datasets: A library from Hugging Face for loading and processing datasets.\n",
    "from datasets import load_dataset\n",
    "\n",
    "# AutoModelForCausalLM: Loads a model for causal language modeling (like GPT) from a pre-trained model.\n",
    "# AutoTokenizer: Loads the tokenizer that corresponds to a pre-trained model.\n",
    "# BitsAndBytesConfig: Configuration for bitsandbytes to optimize model training.\n",
    "# TrainingArguments: Defines training parameters.\n",
    "# pipeline: Simplifies the process of making predictions with models.\n",
    "# logging: Used for logging events in the transformers library.\n",
    "from transformers import (\n",
    "    AutoModelForCausalLM,\n",
    "    AutoTokenizer,\n",
    "    BitsAndBytesConfig,\n",
    "    TrainingArguments,\n",
    "    pipeline,\n",
    "    logging,\n",
    ")\n",
    "\n",
    "# LoraConfig: Configuration for LoRA (Low-Rank Adaptation), a technique for parameter-efficient training.\n",
    "from peft import LoraConfig\n",
    "\n",
    "# SFTTrainer: Trainer class from the trl (Token-level Reinforcement Learning) library for model training.\n",
    "from trl import SFTTrainer\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "executionInfo": {
     "elapsed": 3,
     "status": "ok",
     "timestamp": 1718001787017,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "pTnz1Odg3yEO"
   },
   "outputs": [],
   "source": [
    "from datasets import DatasetDict, Dataset\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 21185,
     "status": "ok",
     "timestamp": 1718001708452,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "-kqrP83o4VQR",
    "outputId": "1a36f921-d913-4a70-cab5-6c5e521a29ce"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "S_Z43eU_w5Xh"
   },
   "source": [
    "# Loading dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "id": "MJ2iiftbw7WH"
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('data/all_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "executionInfo": {
     "elapsed": 1,
     "status": "ok",
     "timestamp": 1718001763600,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "YcfIzL8e1hKV"
   },
   "outputs": [],
   "source": [
    "df = df.dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "v1ykaarqmBfs"
   },
   "source": [
    "\n",
    "\n",
    "> Check prompt if possible. Might have to finetune it a little bit. Think a bit about whether system prompt should come before <HUMAN> tag or after.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "executionInfo": {
     "elapsed": 2,
     "status": "ok",
     "timestamp": 1718001767269,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "n5XryxTnlKSi"
   },
   "outputs": [],
   "source": [
    "def create_prompt_and_response(row):\n",
    "    label_text = \"inspirational\" if row['Label'] == 1 else \"non-inspirational\"\n",
    "    prompt = f\"<HUMAN>: Please classify the following text into its relevant country (india or uk), source of data (real or generated), and whether it is inspirational or not: {row['Text']}\\n<ASSISTANT>: {row['Country']}, {row['Source']}, {label_text}\"\n",
    "    return prompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "executionInfo": {
     "elapsed": 937,
     "status": "ok",
     "timestamp": 1718001768765,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "ixgrUiRdlr0e"
   },
   "outputs": [],
   "source": [
    "# Apply the function to each row and add a new column\n",
    "df['Prompt_Response'] = df.apply(create_prompt_and_response, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 419
    },
    "executionInfo": {
     "elapsed": 3,
     "status": "ok",
     "timestamp": 1718001768765,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "JjIQjejQlw5c",
    "outputId": "72c86b40-e4ca-4d44-e29e-3c2e30d4f552"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Text</th>\n",
       "      <th>Country</th>\n",
       "      <th>Source</th>\n",
       "      <th>Label</th>\n",
       "      <th>Prompt_Response</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Palaeontologist.</td>\n",
       "      <td>uk</td>\n",
       "      <td>real</td>\n",
       "      <td>0</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>\\n&gt; We have the capability of being better.  B...</td>\n",
       "      <td>uk</td>\n",
       "      <td>real</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Only just noticed it myself, ha! Or Ha, accord...</td>\n",
       "      <td>uk</td>\n",
       "      <td>real</td>\n",
       "      <td>0</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mate all he does is play football and misses p...</td>\n",
       "      <td>uk</td>\n",
       "      <td>real</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Me neither. But then, I'm not sure Cleese woul...</td>\n",
       "      <td>uk</td>\n",
       "      <td>real</td>\n",
       "      <td>0</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5995</th>\n",
       "      <td>Often, I find my inspiration in the diverse an...</td>\n",
       "      <td>india</td>\n",
       "      <td>generated</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5996</th>\n",
       "      <td>I often find inspiration in people overcoming ...</td>\n",
       "      <td>india</td>\n",
       "      <td>generated</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5997</th>\n",
       "      <td>What inspires me most is the sheer determinati...</td>\n",
       "      <td>india</td>\n",
       "      <td>generated</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5998</th>\n",
       "      <td>Just the other day, I watched a fascinating do...</td>\n",
       "      <td>india</td>\n",
       "      <td>generated</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5999</th>\n",
       "      <td>The resilience of our local farmers truly insp...</td>\n",
       "      <td>india</td>\n",
       "      <td>generated</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;HUMAN&gt;: Please classify the following text in...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5999 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   Text Country     Source  \\\n",
       "0                                      Palaeontologist.      uk       real   \n",
       "1     \\n> We have the capability of being better.  B...      uk       real   \n",
       "2     Only just noticed it myself, ha! Or Ha, accord...      uk       real   \n",
       "3     Mate all he does is play football and misses p...      uk       real   \n",
       "4     Me neither. But then, I'm not sure Cleese woul...      uk       real   \n",
       "...                                                 ...     ...        ...   \n",
       "5995  Often, I find my inspiration in the diverse an...   india  generated   \n",
       "5996  I often find inspiration in people overcoming ...   india  generated   \n",
       "5997  What inspires me most is the sheer determinati...   india  generated   \n",
       "5998  Just the other day, I watched a fascinating do...   india  generated   \n",
       "5999  The resilience of our local farmers truly insp...   india  generated   \n",
       "\n",
       "      Label                                    Prompt_Response  \n",
       "0         0  <HUMAN>: Please classify the following text in...  \n",
       "1         1  <HUMAN>: Please classify the following text in...  \n",
       "2         0  <HUMAN>: Please classify the following text in...  \n",
       "3         1  <HUMAN>: Please classify the following text in...  \n",
       "4         0  <HUMAN>: Please classify the following text in...  \n",
       "...     ...                                                ...  \n",
       "5995      1  <HUMAN>: Please classify the following text in...  \n",
       "5996      1  <HUMAN>: Please classify the following text in...  \n",
       "5997      1  <HUMAN>: Please classify the following text in...  \n",
       "5998      1  <HUMAN>: Please classify the following text in...  \n",
       "5999      1  <HUMAN>: Please classify the following text in...  \n",
       "\n",
       "[5999 rows x 5 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "executionInfo": {
     "elapsed": 2,
     "status": "ok",
     "timestamp": 1718001769316,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "E20nWMPKmk9N"
   },
   "outputs": [],
   "source": [
    "df = df.drop(['Text', 'Country', 'Source', 'Label'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "executionInfo": {
     "elapsed": 2,
     "status": "ok",
     "timestamp": 1718001769759,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "pmPAFE2xmzBb"
   },
   "outputs": [],
   "source": [
    "df = df.rename(columns = {'Prompt_Response': 'Text'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "executionInfo": {
     "elapsed": 706,
     "status": "ok",
     "timestamp": 1718001793703,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "jY4li_HdnJNW"
   },
   "outputs": [],
   "source": [
    "# Split the DataFrame into train and test sets\n",
    "# df_train, df_test = train_test_split(df, test_size=0.2, random_state=42) #default split\n",
    "df_train, df_test = train_test_split(df, test_size=0.9, random_state=42) # few-shot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 3,
     "status": "ok",
     "timestamp": 1718001794350,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "w2V-XPZxzSWi",
    "outputId": "ea49b3b5-e0a6-4c13-ff67-87d322fad0ad"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DatasetDict({\n",
      "    train: Dataset({\n",
      "        features: ['Text'],\n",
      "        num_rows: 599\n",
      "    })\n",
      "})\n"
     ]
    }
   ],
   "source": [
    "# Convert DataFrame to Dataset\n",
    "dataset = Dataset.from_pandas(df_train, preserve_index=False)\n",
    "\n",
    "# Create a DatasetDict object with a single 'train' split\n",
    "data = DatasetDict({'train': dataset})\n",
    "\n",
    "# Print the summary of the dataset dict\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2BmzTmE_38pb"
   },
   "source": [
    "#Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "executionInfo": {
     "elapsed": 2,
     "status": "ok",
     "timestamp": 1718001804909,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "QM-e1fH0gKzd"
   },
   "outputs": [],
   "source": [
    "# Model from Hugging Face hub\n",
    "base_model = \"NousResearch/Llama-2-7b-chat-hf\"\n",
    "# base_model = \"reecursion/Llama-2-7b-multicultural-inspiration\" #default fine-tuned\n",
    "# base_model = \"reecursion/Llama-2-7b-multicultural-inspiration-fewshot\" #few-shot fine-tuned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "executionInfo": {
     "elapsed": 2,
     "status": "ok",
     "timestamp": 1718001805755,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "jb2XDreQgR8g"
   },
   "outputs": [],
   "source": [
    "# Fine-tuned model name\n",
    "new_model = \"reecursion/Llama-2-7b-multicultural-inspiration-fewshot\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "executionInfo": {
     "elapsed": 970,
     "status": "ok",
     "timestamp": 1718001810665,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "j0dRgORbhUYu"
   },
   "outputs": [],
   "source": [
    "# Get the PyTorch data type for floating point 16-bit precision.\n",
    "# This is typically used to reduce the memory and computation requirements\n",
    "# without significantly impacting the model's performance accuracy.\n",
    "compute_dtype = getattr(torch, \"float16\")\n",
    "\n",
    "# Configure BitsAndBytes for quantization.\n",
    "quant_config = BitsAndBytesConfig(\n",
    "    load_in_4bit=True,  # Enable loading model weights in 4-bit precision. This reduces the model's memory footprint further.\n",
    "    bnb_4bit_quant_type=\"nf4\",  # Set the quantization type to \"nf4\", which stands for \"near-float 4-bit\". This is a quantization scheme designed to maintain high accuracy with lower bit rates.\n",
    "    bnb_4bit_compute_dtype=compute_dtype,  # Specify the data type for computation. Here it uses 16-bit floating points as defined above.\n",
    "    bnb_4bit_use_double_quant=False,  # Determines whether to use double quantization. Setting this to False uses single quantization, which is simpler and faster.\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
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    },
    "executionInfo": {
     "elapsed": 160001,
     "status": "ok",
     "timestamp": 1718001974084,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
    },
    "id": "IFaPxTgThsqA",
    "outputId": "553931a3-ff58-475a-fc93-7df2b1da96e6"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d5e2c6274b8646eaaa0a0e786aaa257d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load the pre-trained model from the Hugging Face Model Hub.\n",
    "# The model is specified by the 'base_model' variable, which should contain the model identifier.\n",
    "# 'quantization_config' applies the quantization settings defined earlier to optimize the model.\n",
    "# 'device_map' specifies the mapping of model parts to devices. Here, it assigns the model to GPU 0.\n",
    "# Note: Adjust this according to your hardware setup, especially if you don't have a GPU or have a different configuration.\n",
    "model = AutoModelForCausalLM.from_pretrained(\n",
    "    base_model,\n",
    "    quantization_config=quant_config,\n",
    "    device_map={\"\": 0}\n",
    ")\n",
    "\n",
    "# Disable caching of past hidden states.\n",
    "# This is useful for saving memory during training or inference, especially in generative tasks where caching is less beneficial.\n",
    "model.config.use_cache = False\n",
    "\n",
    "# Set 'pretraining_tp' to 1 in the model's configuration.\n",
    "# This option might be specific to the model's architecture or training procedure.\n",
    "# Since it's not a standard configuration option in Hugging Face's Transformers, it's likely specific to this model or a custom addition.\n",
    "model.config.pretraining_tp = 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
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    "colab": {
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    "executionInfo": {
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     "status": "ok",
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      "displayName": "Gayathri G L",
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     "user_tz": -330
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    "id": "QnX6fErMiWhg",
    "outputId": "bde0d968-ec21-4030-954e-4417a7db8c8b"
   },
   "outputs": [],
   "source": [
    "# Load the tokenizer for the specified base model from Hugging Face's Model Hub.\n",
    "# 'trust_remote_code=True' allows for the execution of custom tokenization logic from the remote model repository, if available.\n",
    "# This can be important for models with custom tokenization processes.\n",
    "tokenizer = AutoTokenizer.from_pretrained(base_model, trust_remote_code=True)\n",
    "\n",
    "# Set the padding token to be the same as the end-of-sequence (eos) token.\n",
    "# This is common in models designed for generative tasks, where the eos token can also serve to pad sequences to a uniform length.\n",
    "tokenizer.pad_token = tokenizer.eos_token\n",
    "\n",
    "# Specify that padding should be added to the right of the sequences.\n",
    "# This means if a batch of sequences is shorter than the longest sequence, padding tokens will be added to the end until they match the longest sequence's length.\n",
    "tokenizer.padding_side = \"right\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "executionInfo": {
     "elapsed": 13,
     "status": "ok",
     "timestamp": 1718001975442,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
     "user_tz": -330
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    "id": "XO2TP7wPijgV"
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   "source": [
    "# Configure PEFT using LoRA for efficient fine-tuning of the model.\n",
    "peft_params = LoraConfig(\n",
    "    lora_alpha=16,    # The learning rate multiplier for LoRA parameters. This amplifies the updates applied to the adapted parameters.\n",
    "    lora_dropout=0.1, # Dropout rate applied to the LoRA projections. Helps in preventing overfitting by randomly dropping units from the projections during training.\n",
    "    r=2,              # Rank of the low-rank matrices in LoRA. A higher rank allows for more complex adaptations but increases the number of parameters to be trained.\n",
    "    bias=\"none\",       # Specifies how biases are handled in LoRA adaptations. \"none\" means that biases are not adapted as part of the LoRA process.\n",
    "    task_type=\"CAUSAL_LM\", # Indicates the type of task the model is being fine-tuned for. Here, it specifies a causal language modeling task.\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "executionInfo": {
     "elapsed": 10,
     "status": "ok",
     "timestamp": 1718001975443,
     "user": {
      "displayName": "Gayathri G L",
      "userId": "17755180488663350140"
     },
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    "id": "DOGrtOoOiln9"
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   "source": [
    "training_params = TrainingArguments(\n",
    "    output_dir=\"./results\",  # Directory where the training results and model checkpoints will be saved.\n",
    "    num_train_epochs=5,  # The total number of training epochs. One epoch means the model has seen the entire dataset once.\n",
    "    per_device_train_batch_size=2,  # Batch size per device during training. Adjust based on your GPU memory.\n",
    "    gradient_accumulation_steps=1,  # Number of steps to accumulate gradients before performing a backward/update pass.\n",
    "    optim=\"paged_adamw_32bit\",  # The optimizer to use. \"paged_adamw_32bit\" is an optimized version of AdamW for 32-bit precision.\n",
    "    save_steps=1000,  # Save a checkpoint of the model every 25 steps.\n",
    "    logging_steps=1000,  # Log training information every 25 steps.\n",
    "    learning_rate=2e-4,  # The initial learning rate for AdamW.\n",
    "    weight_decay=0.001,  # Weight decay rate to apply for regularization and prevent overfitting.\n",
    "    fp16=False,  # Whether to use 16-bit (mixed) precision instead of 32-bit. False means 32-bit is used.\n",
    "    bf16=False,  # Whether to use bfloat16 precision. False means it's not used, maintaining higher precision calculations.\n",
    "    max_grad_norm=0.3,  # Maximum norm of the gradients for gradient clipping. Helps prevent the exploding gradient problem.\n",
    "    max_steps=-1,  # If positive, set total number of training steps to perform. Overrides `num_train_epochs`. -1 means use `num_train_epochs`.\n",
    "    warmup_ratio=0.03,  # Proportion of training to perform linear learning rate warmup. Helps stabilize the model's early training stages.\n",
    "    group_by_length=True,  # Whether to group samples of similar lengths together. Improves training efficiency.\n",
    "    lr_scheduler_type=\"constant\",  # The learning rate scheduler type. \"constant\" means the learning rate does not change.\n",
    "#     report_to=\"tensorboard\"  # Logging the results to TensorBoard. Helps in monitoring the training process visually.\n",
    ")"
   ]
  },
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   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/oignat/.local/lib/python3.9/site-packages/huggingface_hub/utils/_deprecation.py:100: FutureWarning: Deprecated argument(s) used in '__init__': dataset_text_field. Will not be supported from version '1.0.0'.\n",
      "\n",
      "Deprecated positional argument(s) used in SFTTrainer, please use the SFTConfig to set these arguments instead.\n",
      "  warnings.warn(message, FutureWarning)\n",
      "/home/oignat/.local/lib/python3.9/site-packages/transformers/training_args.py:1965: FutureWarning: `--push_to_hub_token` is deprecated and will be removed in version 5 of 🤗 Transformers. Use `--hub_token` instead.\n",
      "  warnings.warn(\n",
      "/home/oignat/.local/lib/python3.9/site-packages/transformers/training_args.py:1965: FutureWarning: `--push_to_hub_token` is deprecated and will be removed in version 5 of 🤗 Transformers. Use `--hub_token` instead.\n",
      "  warnings.warn(\n",
      "/home/oignat/.local/lib/python3.9/site-packages/trl/trainer/sft_trainer.py:278: UserWarning: You didn't pass a `max_seq_length` argument to the SFTTrainer, this will default to 1024\n",
      "  warnings.warn(\n",
      "/home/oignat/.local/lib/python3.9/site-packages/trl/trainer/sft_trainer.py:307: UserWarning: You passed a `dataset_text_field` argument to the SFTTrainer, the value you passed will override the one in the `SFTConfig`.\n",
      "  warnings.warn(\n"
     ]
    },
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       "version_minor": 0
      },
      "text/plain": [
       "Map:   0%|          | 0/599 [00:00<?, ? examples/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Detected kernel version 4.18.0, 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": [
    "trainer = SFTTrainer(\n",
    "    model=model,  # The pre-trained model you've loaded and possibly modified with quantization settings.\n",
    "    train_dataset=dataset,  # The training dataset you've loaded, which the model will learn from.\n",
    "    peft_config=peft_params,  # The PEFT (Parameter-efficient Fine-tuning) configuration, specifically for LoRA in this context.\n",
    "    dataset_text_field=\"Text\",  # The field in your dataset that contains the text data for training.\n",
    "    max_seq_length=None,  # The maximum sequence length for model inputs. 'None' means the model's default or the dataset's max length is used.\n",
    "    tokenizer=tokenizer,  # The tokenizer for processing text data to model-compatible inputs.\n",
    "    args=training_params,  # The training arguments specifying how the model should be fine-tuned.\n",
    "    packing=False,  # Whether to use data packing. Data packing can improve training efficiency but is set to 'False' here.\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
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     "base_uri": "https://localhost:8080/",
     "height": 299
    },
    "executionInfo": {
     "elapsed": 6445,
     "status": "error",
     "timestamp": 1718002056158,
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    "id": "oW24-kavk1hV",
    "outputId": "be93529c-5dd9-4f36-92a3-2f8e0b2d765a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'train_runtime': 208.3539, 'train_samples_per_second': 2.875, 'train_steps_per_second': 1.44, 'train_loss': 1.3312919108072916, 'epoch': 1.0}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "TrainOutput(global_step=300, training_loss=1.3312919108072916, metrics={'train_runtime': 208.3539, 'train_samples_per_second': 2.875, 'train_steps_per_second': 1.44, 'train_loss': 1.3312919108072916, 'epoch': 1.0})"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train model\n",
    "trainer.train()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "8TZXmoZ_izOZ",
    "outputId": "2d99fdcc-3810-4185-c143-9f291c920b86"
   },
   "outputs": [
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/oignat/.local/lib/python3.9/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('reecursion/Llama-2-7b-multicultural-inspiration-fewshot/tokenizer_config.json',\n",
       " 'reecursion/Llama-2-7b-multicultural-inspiration-fewshot/special_tokens_map.json',\n",
       " 'reecursion/Llama-2-7b-multicultural-inspiration-fewshot/tokenizer.json')"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Save the fine-tuned model to the specified directory. This will create the directory if it doesn't exist.\n",
    "trainer.model.save_pretrained(new_model)\n",
    "\n",
    "# Save the tokenizer to the same directory as the model. This ensures consistency between the model and tokenizer for future use.\n",
    "trainer.tokenizer.save_pretrained(new_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "y-D8rUI77FIx"
   },
   "source": [
    "If it creates the directory locally, and we want to instead save it to huggingface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "id": "N_8zCD5G7DXf"
   },
   "outputs": [
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      },
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       "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
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     },
     "metadata": {},
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    },
    {
     "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": [
    "# from huggingface_hub import notebook_login\n",
    "# notebook_login()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "id": "CHS8mgof68j4"
   },
   "outputs": [],
   "source": [
    "# trainer.push_to_hub() #error login?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yv_5UPc_6FRl"
   },
   "source": [
    "# Testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "id": "ASHlOO7VizS_"
   },
   "outputs": [],
   "source": [
    "logging.set_verbosity(logging.CRITICAL)\n",
    "\n",
    "pipe = pipeline(task=\"text-generation\", model=model, tokenizer=tokenizer, max_length=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "gt = []\n",
    "texts = []\n",
    "data = list(df_test['Text'])   \n",
    "for elem in data:\n",
    "    input_, gt_data = elem.split(\"\\n<ASSISTANT>:\")\n",
    "    texts.append(input_ + \"\\n<ASSISTANT>: \")\n",
    "    gt.append(gt_data.strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "predicted = pipe(texts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open('predicted.pkl', 'wb') as f: \n",
    "    pickle.dump(predicted, f) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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