{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tqdm in ./.venv/lib/python3.10/site-packages (4.66.1)\n",
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      "Requirement already satisfied: pyarrow in ./.venv/lib/python3.10/site-packages (15.0.0)\n",
      "Collecting torch\n",
      "  Downloading torch-2.2.0-cp310-cp310-manylinux1_x86_64.whl (755.5 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m755.5/755.5 MB\u001b[0m \u001b[31m3.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
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      "Collecting nvidia-cusparse-cu12==12.1.0.106\n",
      "  Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n",
      "Collecting nvidia-cuda-runtime-cu12==12.1.105\n",
      "  Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
      "Collecting triton==2.2.0\n",
      "  Using cached triton-2.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (167.9 MB)\n",
      "Collecting nvidia-cublas-cu12==12.1.3.1\n",
      "  Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
      "Collecting jinja2\n",
      "  Using cached Jinja2-3.1.3-py3-none-any.whl (133 kB)\n",
      "Collecting nvidia-nvtx-cu12==12.1.105\n",
      "  Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n",
      "Collecting sympy\n",
      "  Using cached sympy-1.12-py3-none-any.whl (5.7 MB)\n",
      "Requirement already satisfied: typing-extensions>=4.8.0 in ./.venv/lib/python3.10/site-packages (from torch) (4.9.0)\n",
      "Collecting nvidia-cuda-cupti-cu12==12.1.105\n",
      "  Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n",
      "Collecting nvidia-cusolver-cu12==11.4.5.107\n",
      "  Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
      "Collecting nvidia-cufft-cu12==11.0.2.54\n",
      "  Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
      "Requirement already satisfied: fsspec in ./.venv/lib/python3.10/site-packages (from torch) (2023.12.2)\n",
      "Collecting nvidia-cuda-nvrtc-cu12==12.1.105\n",
      "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
      "Collecting networkx\n",
      "  Using cached networkx-3.2.1-py3-none-any.whl (1.6 MB)\n",
      "Collecting nvidia-nccl-cu12==2.19.3\n",
      "  Downloading nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl (166.0 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m166.0/166.0 MB\u001b[0m \u001b[31m13.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
      "\u001b[?25hCollecting nvidia-cudnn-cu12==8.9.2.26\n",
      "  Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n",
      "Collecting nvidia-curand-cu12==10.3.2.106\n",
      "  Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
      "Collecting nvidia-nvjitlink-cu12\n",
      "  Using cached nvidia_nvjitlink_cu12-12.3.101-py3-none-manylinux1_x86_64.whl (20.5 MB)\n",
      "Requirement already satisfied: six>=1.5 in ./.venv/lib/python3.10/site-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n",
      "Collecting MarkupSafe>=2.0\n",
      "  Using cached MarkupSafe-2.1.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (25 kB)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in ./.venv/lib/python3.10/site-packages (from requests->transformers) (2.2.0)\n",
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      "Collecting mpmath>=0.19\n",
      "  Using cached mpmath-1.3.0-py3-none-any.whl (536 kB)\n",
      "Installing collected packages: mpmath, triton, sympy, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, networkx, MarkupSafe, nvidia-cusparse-cu12, nvidia-cudnn-cu12, jinja2, nvidia-cusolver-cu12, torch\n",
      "Successfully installed MarkupSafe-2.1.4 jinja2-3.1.3 mpmath-1.3.0 networkx-3.2.1 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.3.101 nvidia-nvtx-cu12-12.1.105 sympy-1.12 torch-2.2.0 triton-2.2.0\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.3.2\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install tqdm transformers pandas pyarrow torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "import torch\n",
    "import os\n",
    "import re\n",
    "import shutil\n",
    "from tqdm import tqdm\n",
    "from transformers import AutoTokenizer, AutoModelForCausalLM\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_name = \"Dans-DiscountModels/Dans-StructureEvaluator-Small\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "ename": "RuntimeError",
     "evalue": "Failed to import transformers.models.mistral.modeling_mistral because of the following error (look up to see its traceback):\nmodule 'torch._subclasses' has no attribute 'functional_tensor'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/transformers/utils/import_utils.py:1364\u001b[0m, in \u001b[0;36m_LazyModule._get_module\u001b[0;34m(self, module_name)\u001b[0m\n\u001b[1;32m   1363\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1364\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mimportlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimport_module\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m.\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mmodule_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;18;43m__name__\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1365\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[0;32m~/.proto/tools/python/3.10.11/install/lib/python3.10/importlib/__init__.py:126\u001b[0m, in \u001b[0;36mimport_module\u001b[0;34m(name, package)\u001b[0m\n\u001b[1;32m    125\u001b[0m         level \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m--> 126\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_bootstrap\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_gcd_import\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m[\u001b[49m\u001b[43mlevel\u001b[49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpackage\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlevel\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m<frozen importlib._bootstrap>:1050\u001b[0m, in \u001b[0;36m_gcd_import\u001b[0;34m(name, package, level)\u001b[0m\n",
      "File \u001b[0;32m<frozen importlib._bootstrap>:1027\u001b[0m, in \u001b[0;36m_find_and_load\u001b[0;34m(name, import_)\u001b[0m\n",
      "File \u001b[0;32m<frozen importlib._bootstrap>:1006\u001b[0m, in \u001b[0;36m_find_and_load_unlocked\u001b[0;34m(name, import_)\u001b[0m\n",
      "File \u001b[0;32m<frozen importlib._bootstrap>:688\u001b[0m, in \u001b[0;36m_load_unlocked\u001b[0;34m(spec)\u001b[0m\n",
      "File \u001b[0;32m<frozen importlib._bootstrap_external>:883\u001b[0m, in \u001b[0;36mexec_module\u001b[0;34m(self, module)\u001b[0m\n",
      "File \u001b[0;32m<frozen importlib._bootstrap>:241\u001b[0m, in \u001b[0;36m_call_with_frames_removed\u001b[0;34m(f, *args, **kwds)\u001b[0m\n",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/transformers/models/mistral/modeling_mistral.py:28\u001b[0m\n\u001b[1;32m     27\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mnn\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mfunctional\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mF\u001b[39;00m\n\u001b[0;32m---> 28\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mutils\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcheckpoint\u001b[39;00m\n\u001b[1;32m     29\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtorch\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m nn\n",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/torch/utils/checkpoint.py:1169\u001b[0m\n\u001b[1;32m   1163\u001b[0m \u001b[38;5;66;03m# NOTE: torch.utils.checkpoint internal logic will call these two functions unknown number of times\u001b[39;00m\n\u001b[1;32m   1164\u001b[0m \u001b[38;5;66;03m# (i.e. there could be _CachedTorchDispatchMode calls that doesn't map to a _CachingTorchDispatchMode call),\u001b[39;00m\n\u001b[1;32m   1165\u001b[0m \u001b[38;5;66;03m# so we ignore these ops and just always recompute them.\u001b[39;00m\n\u001b[1;32m   1166\u001b[0m _ignored_ops \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m   1167\u001b[0m     torch\u001b[38;5;241m.\u001b[39mops\u001b[38;5;241m.\u001b[39mprim\u001b[38;5;241m.\u001b[39mdevice\u001b[38;5;241m.\u001b[39mdefault,\n\u001b[1;32m   1168\u001b[0m     torch\u001b[38;5;241m.\u001b[39mops\u001b[38;5;241m.\u001b[39maten\u001b[38;5;241m.\u001b[39mdetach\u001b[38;5;241m.\u001b[39mdefault,\n\u001b[0;32m-> 1169\u001b[0m } \u001b[38;5;241m|\u001b[39m \u001b[38;5;28mset\u001b[39m(\u001b[43mtorch\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_subclasses\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfunctional_tensor\u001b[49m\u001b[38;5;241m.\u001b[39mFunctionalTensor\u001b[38;5;241m.\u001b[39mmetadata_fns)\n\u001b[1;32m   1172\u001b[0m \u001b[38;5;28;01mclass\u001b[39;00m \u001b[38;5;21;01m_CachingTorchDispatchMode\u001b[39;00m(TorchDispatchMode):\n",
      "\u001b[0;31mAttributeError\u001b[0m: module 'torch._subclasses' has no attribute 'functional_tensor'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[15], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mAutoModelForCausalLM\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_pretrained\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice_map\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcuda\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m tokenizer \u001b[38;5;241m=\u001b[39m AutoTokenizer\u001b[38;5;241m.\u001b[39mfrom_pretrained(model_name)\n",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:565\u001b[0m, in \u001b[0;36m_BaseAutoModelClass.from_pretrained\u001b[0;34m(cls, pretrained_model_name_or_path, *model_args, **kwargs)\u001b[0m\n\u001b[1;32m    561\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m model_class\u001b[38;5;241m.\u001b[39mfrom_pretrained(\n\u001b[1;32m    562\u001b[0m         pretrained_model_name_or_path, \u001b[38;5;241m*\u001b[39mmodel_args, config\u001b[38;5;241m=\u001b[39mconfig, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mhub_kwargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs\n\u001b[1;32m    563\u001b[0m     )\n\u001b[1;32m    564\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mtype\u001b[39m(config) \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys():\n\u001b[0;32m--> 565\u001b[0m     model_class \u001b[38;5;241m=\u001b[39m \u001b[43m_get_model_class\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mcls\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_model_mapping\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    566\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m model_class\u001b[38;5;241m.\u001b[39mfrom_pretrained(\n\u001b[1;32m    567\u001b[0m         pretrained_model_name_or_path, \u001b[38;5;241m*\u001b[39mmodel_args, config\u001b[38;5;241m=\u001b[39mconfig, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mhub_kwargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs\n\u001b[1;32m    568\u001b[0m     )\n\u001b[1;32m    569\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    570\u001b[0m     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnrecognized configuration class \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mconfig\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m for this kind of AutoModel: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    571\u001b[0m     \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mModel type should be one of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(c\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mfor\u001b[39;00m\u001b[38;5;250m \u001b[39mc\u001b[38;5;250m \u001b[39m\u001b[38;5;129;01min\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping\u001b[38;5;241m.\u001b[39mkeys())\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    572\u001b[0m )\n",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:387\u001b[0m, in \u001b[0;36m_get_model_class\u001b[0;34m(config, model_mapping)\u001b[0m\n\u001b[1;32m    386\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_get_model_class\u001b[39m(config, model_mapping):\n\u001b[0;32m--> 387\u001b[0m     supported_models \u001b[38;5;241m=\u001b[39m \u001b[43mmodel_mapping\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mtype\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m    388\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(supported_models, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m)):\n\u001b[1;32m    389\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m supported_models\n",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:740\u001b[0m, in \u001b[0;36m_LazyAutoMapping.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m    738\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m model_type \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping:\n\u001b[1;32m    739\u001b[0m     model_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_model_mapping[model_type]\n\u001b[0;32m--> 740\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_load_attr_from_module\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodel_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel_name\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    742\u001b[0m \u001b[38;5;66;03m# Maybe there was several model types associated with this config.\u001b[39;00m\n\u001b[1;32m    743\u001b[0m model_types \u001b[38;5;241m=\u001b[39m [k \u001b[38;5;28;01mfor\u001b[39;00m k, v \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_config_mapping\u001b[38;5;241m.\u001b[39mitems() \u001b[38;5;28;01mif\u001b[39;00m v \u001b[38;5;241m==\u001b[39m key\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m]\n",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:754\u001b[0m, in \u001b[0;36m_LazyAutoMapping._load_attr_from_module\u001b[0;34m(self, model_type, attr)\u001b[0m\n\u001b[1;32m    752\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m module_name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_modules:\n\u001b[1;32m    753\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_modules[module_name] \u001b[38;5;241m=\u001b[39m importlib\u001b[38;5;241m.\u001b[39mimport_module(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmodule_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtransformers.models\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m--> 754\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mgetattribute_from_module\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_modules\u001b[49m\u001b[43m[\u001b[49m\u001b[43mmodule_name\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattr\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:698\u001b[0m, in \u001b[0;36mgetattribute_from_module\u001b[0;34m(module, attr)\u001b[0m\n\u001b[1;32m    696\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(attr, \u001b[38;5;28mtuple\u001b[39m):\n\u001b[1;32m    697\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtuple\u001b[39m(getattribute_from_module(module, a) \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m attr)\n\u001b[0;32m--> 698\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28;43mhasattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mmodule\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mattr\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m    699\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(module, attr)\n\u001b[1;32m    700\u001b[0m \u001b[38;5;66;03m# Some of the mappings have entries model_type -> object of another model type. In that case we try to grab the\u001b[39;00m\n\u001b[1;32m    701\u001b[0m \u001b[38;5;66;03m# object at the top level.\u001b[39;00m\n",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/transformers/utils/import_utils.py:1354\u001b[0m, in \u001b[0;36m_LazyModule.__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m   1352\u001b[0m     value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_module(name)\n\u001b[1;32m   1353\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m name \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_class_to_module\u001b[38;5;241m.\u001b[39mkeys():\n\u001b[0;32m-> 1354\u001b[0m     module \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_module\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_class_to_module\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1355\u001b[0m     value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(module, name)\n\u001b[1;32m   1356\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "File \u001b[0;32m~/ai/llm/datasets/NyxKrage_bambisleep/.venv/lib/python3.10/site-packages/transformers/utils/import_utils.py:1366\u001b[0m, in \u001b[0;36m_LazyModule._get_module\u001b[0;34m(self, module_name)\u001b[0m\n\u001b[1;32m   1364\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m importlib\u001b[38;5;241m.\u001b[39mimport_module(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m module_name, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m)\n\u001b[1;32m   1365\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m-> 1366\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m   1367\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFailed to import \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmodule_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m because of the following error (look up to see its\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1368\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m traceback):\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m{\u001b[39;00me\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1369\u001b[0m     ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n",
      "\u001b[0;31mRuntimeError\u001b[0m: Failed to import transformers.models.mistral.modeling_mistral because of the following error (look up to see its traceback):\nmodule 'torch._subclasses' has no attribute 'functional_tensor'"
     ]
    }
   ],
   "source": [
    "model = AutoModelForCausalLM.from_pretrained(model_name, device_map = \"cuda\")\n",
    "tokenizer = AutoTokenizer.from_pretrained(model_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_perplexity(text):\n",
    "    input_ids = torch.tensor([tokenizer.encode(text)]).to(\"cuda:0\")\n",
    "\n",
    "    model.eval()\n",
    "\n",
    "    with torch.no_grad():\n",
    "        outputs = model(input_ids, labels=input_ids)\n",
    "        loss = outputs[0]\n",
    "\n",
    "    del outputs\n",
    "    torch.cuda.empty_cache()\n",
    "\n",
    "    return torch.exp(loss).item()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_data_into_windows(data):\n",
    "    lines = data.splitlines()\n",
    "    windows = []\n",
    "\n",
    "    for i in range(1, len(lines)):\n",
    "        # Get the previous line and current line\n",
    "        prev_line = lines[i - 1]\n",
    "        curr_line = lines[i]\n",
    "\n",
    "        # If it's the first line or the last line, don't split it\n",
    "        if i == 1:\n",
    "            mid_index = len(curr_line) // 2\n",
    "            first_half = curr_line[:mid_index]\n",
    "            windows.append((prev_line, first_half))\n",
    "        elif i == len(lines) - 1:\n",
    "            mid_index = len(prev_line) // 2\n",
    "            second_half = prev_line[mid_index:]\n",
    "            windows.append((second_half, curr_line))\n",
    "        else:\n",
    "            # Split the current line into two halves\n",
    "            curr_mid_index = len(curr_line) // 2\n",
    "            prev_mid_index = len(prev_line) // 2\n",
    "            first_half = curr_line[:curr_mid_index]\n",
    "            second_half = prev_line[prev_mid_index:]\n",
    "\n",
    "            windows.append((second_half, first_half))\n",
    "    return windows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def join_lines(lines):\n",
    "    with_space = lines[0] + \" \" + lines[1]\n",
    "    without_space = lines[0] + lines[1]\n",
    "    with_space_perplexity = calculate_perplexity(with_space)\n",
    "    without_space_perplexity = calculate_perplexity(without_space)\n",
    "    if with_space_perplexity < without_space_perplexity:\n",
    "        return with_space\n",
    "    else:\n",
    "        return without_space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def join_windows(windows):\n",
    "    output = \"\"\n",
    "    for window in windows:\n",
    "        output += join_lines(window)\n",
    "    return output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = glob.glob(\"orig/*.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove all non-original files that have an original file associated with them\n",
    "copy_files = {}\n",
    "for file in files:\n",
    "    if file in copy_files:\n",
    "        continue\n",
    "    if \" (_ORIGINAL SERIES)\" in file:\n",
    "        original_file = file.replace(\" (_ORIGINAL SERIES)\", \"\")\n",
    "        copy_files[file] = original_file.replace(\"orig/\", \"dedup/\")\n",
    "    elif \" (_UNCHANGED)\" in file:\n",
    "        original_file = file.replace(\" (_UNCHANGED)\", \"\")\n",
    "        copy_files[file] = original_file.replace(\"orig/\", \"dedup/\")\n",
    "    else:\n",
    "        copy_files[file] = file.replace(\"orig/\", \"dedup/\")\n",
    "\n",
    "# for all values in copy_files, if the value contains parentheses and the filename without them is already a value in copy_files remove it\n",
    "to_remove = []\n",
    "for kv in copy_files.items():\n",
    "    if \"(\" in kv[1]:\n",
    "        original_file = re.sub(r\" \\(.+\\)\", \"\", kv[1])\n",
    "        if original_file in copy_files.values():\n",
    "            to_remove.append(kv[0])\n",
    "\n",
    "for file in to_remove:\n",
    "    del copy_files[file]\n",
    "\n",
    "for kv in copy_files.items():\n",
    "    if \"+\" in kv[1]:\n",
    "        original_file = re.sub(r\" \\(.+\\)\", \"\", kv[1])\n",
    "        copy_files[kv[0]] = original_file\n",
    "\n",
    "to_remove.clear()\n",
    "for kv in copy_files.items():\n",
    "    if \"(\" in kv[1]:\n",
    "        original_file = re.sub(r\" \\(.+\\)\", \"\", kv[1])\n",
    "        if original_file in copy_files.values():\n",
    "            to_remove.append(kv[0])\n",
    "\n",
    "for file in to_remove:\n",
    "    del copy_files[file]\n",
    "\n",
    "for kv in copy_files.items():\n",
    "    if \"(Full)\" in kv[1]:\n",
    "        original_file = re.sub(r\" \\(.+\\)\", \"\", kv[1])\n",
    "        if original_file not in copy_files.values():\n",
    "            copy_files[kv[0]] = original_file\n",
    "\n",
    "to_remove.clear()\n",
    "for kv in copy_files.items():\n",
    "    if \"(\" in kv[1]:\n",
    "        to_remove.append(kv[0])\n",
    "\n",
    "for file in to_remove:\n",
    "    del copy_files[file]\n",
    "\n",
    "# copy files to new directory\n",
    "shutil.rmtree(\"dedup\", ignore_errors=True)\n",
    "os.makedirs(\"dedup\", exist_ok=True)\n",
    "for kv in copy_files.items():\n",
    "    shutil.copy(kv[0], kv[1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = glob.glob(\"dedup/*.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove all empty lines in the dedup files\n",
    "shutil.rmtree(\"dedup_no_empty\", ignore_errors=True)\n",
    "os.makedirs(\"dedup_no_empty\", exist_ok=True)\n",
    "for file in files:\n",
    "    with open(file, \"r\") as f:\n",
    "        data = f.read()\n",
    "    while \"\\n\\n\" in data:\n",
    "        data = data.replace(\"\\n\\n\", \"\\n\")\n",
    "    new_file = file.replace(\"dedup\", \"dedup_no_empty\")\n",
    "    with open(new_file, \"w\") as f:\n",
    "        f.write(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = glob.glob(\"dedup_no_empty/*.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 30/30 [01:56<00:00,  3.88s/it]\n"
     ]
    }
   ],
   "source": [
    "shutil.rmtree(\"joined\", ignore_errors=True)\n",
    "os.makedirs(\"joined\", exist_ok=True)\n",
    "for file in tqdm(files):\n",
    "    with open(file, \"r\") as f:\n",
    "        data = f.read()\n",
    "    windows = split_data_into_windows(data)\n",
    "    joined = join_windows(windows)\n",
    "    new_file = file.replace(\"dedup_no_empty\", \"joined\")\n",
    "    # in joined make sure there is a space after every period or comma\n",
    "    joined = joined\n",
    "    \n",
    "    with open(new_file, \"w\") as f:\n",
    "        f.write(joined)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = glob.glob(\"joined/*.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 30/30 [00:00<00:00, 8242.44it/s]\n"
     ]
    }
   ],
   "source": [
    "shutil.rmtree(\"cleaned\", ignore_errors=True)\n",
    "os.makedirs(\"cleaned\", exist_ok=True)\n",
    "for file in tqdm(files):\n",
    "    with open(file, \"r\") as f:\n",
    "        data = f.read()\n",
    "    data = data.replace(\".\", \". \").replace(\",\", \", \").replace(\"  \", \" \").replace('\"', \"\")\n",
    "    new_file = file.replace(\"joined\", \"cleaned\")\n",
    "    with open(new_file, \"w\") as f:\n",
    "        f.write(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = glob.glob(\"cleaned/*.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 30/30 [00:00<00:00, 44779.05it/s]\n"
     ]
    },
    {
     "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Just Bambi Sleep. Deeper and deeper. Feeling b...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Every command Bambi has accepted in this sessi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Feeling wonderfully obedient Bambi. Perfectly ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>That's right. Doing so well. Like a pretty gir...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bambi is completely susceptible to hypnosis. A...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>That's right Bambi. Eyelids fluttering like a ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>That's right Bambi feeling so good. Just drift...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Now as Bambi Sleeps deeper and deeper. Fuzzier...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bambi Sleep Now. And Bambi suddenly finds hers...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Bambi is a perfect fuckable fashion puppet. A ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Drifting deeper and deeper Bambi. More and mor...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>[Various voices looping conditioning phrases]S...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Bambi Sleep Now. Just Bambi Sleep. Every time ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Feeling the need to be Primped And Pampered.  ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>That's a Good Girl Bambi. Feeling more and mor...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>And Bambi is so perfectly trapped in her bimbo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>And Bambi every time you go so deeply into tra...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Bambi Freeze. That's a Good Girl. All thoughts...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Such a Good Girl Bambi. Feeling so much pleasu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Soon it will be time for you to awaken Bambi. ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>That's right Bambi. Feeling so wonderful. Feel...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Take a deep breath Bambi. Hold it for a moment...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>That's a Good Girl Bambi. Feeling more and mor...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Bambi Sleep now. No resistance, must sleep now...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Slipping deeper and deeper now Bambi. Just tak...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Hi sweetie! Welcome to the Sleepy Girl Salon B...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>It's time to go so much deeper Bambi. And ther...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>That's right. Deeply asleep now Bambi. Complet...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Bambi can feel her perfect heaving titties now...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>That's it Bambi. So peaceful. So perfect. So b...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 text\n",
       "0   Just Bambi Sleep. Deeper and deeper. Feeling b...\n",
       "1   Every command Bambi has accepted in this sessi...\n",
       "2   Feeling wonderfully obedient Bambi. Perfectly ...\n",
       "3   That's right. Doing so well. Like a pretty gir...\n",
       "4   Bambi is completely susceptible to hypnosis. A...\n",
       "5   That's right Bambi. Eyelids fluttering like a ...\n",
       "6   That's right Bambi feeling so good. Just drift...\n",
       "7   Now as Bambi Sleeps deeper and deeper. Fuzzier...\n",
       "8   Bambi Sleep Now. And Bambi suddenly finds hers...\n",
       "9   Bambi is a perfect fuckable fashion puppet. A ...\n",
       "10  Drifting deeper and deeper Bambi. More and mor...\n",
       "11  [Various voices looping conditioning phrases]S...\n",
       "12  Bambi Sleep Now. Just Bambi Sleep. Every time ...\n",
       "13  Feeling the need to be Primped And Pampered.  ...\n",
       "14  That's a Good Girl Bambi. Feeling more and mor...\n",
       "15  And Bambi is so perfectly trapped in her bimbo...\n",
       "16  And Bambi every time you go so deeply into tra...\n",
       "17  Bambi Freeze. That's a Good Girl. All thoughts...\n",
       "18  Such a Good Girl Bambi. Feeling so much pleasu...\n",
       "19  Soon it will be time for you to awaken Bambi. ...\n",
       "20  That's right Bambi. Feeling so wonderful. Feel...\n",
       "21  Take a deep breath Bambi. Hold it for a moment...\n",
       "22  That's a Good Girl Bambi. Feeling more and mor...\n",
       "23  Bambi Sleep now. No resistance, must sleep now...\n",
       "24  Slipping deeper and deeper now Bambi. Just tak...\n",
       "25  Hi sweetie! Welcome to the Sleepy Girl Salon B...\n",
       "26  It's time to go so much deeper Bambi. And ther...\n",
       "27  That's right. Deeply asleep now Bambi. Complet...\n",
       "28  Bambi can feel her perfect heaving titties now...\n",
       "29  That's it Bambi. So peaceful. So perfect. So b..."
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load each file as a row with the text in a column called text\n",
    "texts = []\n",
    "full_text = \"\"\n",
    "for file in tqdm(files):\n",
    "    with open(file, \"r\") as f:\n",
    "        data = f.read()\n",
    "    texts.append(data)\n",
    "    full_text += data + \"\\n\"\n",
    "\n",
    "file = \"bambisleep.parquet\"\n",
    "df = pd.DataFrame({ \"text\": texts }, columns=[\"text\"])\n",
    "df.to_parquet(file)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "tokenizer_config.json: 100%|██████████| 1.29k/1.29k [00:00<00:00, 9.67MB/s]\n",
      "tokenizer.model: 100%|██████████| 500k/500k [00:00<00:00, 5.74MB/s]\n",
      "tokenizer.json: 100%|██████████| 1.84M/1.84M [00:00<00:00, 4.03MB/s]\n",
      "special_tokens_map.json: 100%|██████████| 551/551 [00:00<00:00, 4.15MB/s]\n"
     ]
    }
   ],
   "source": [
    "end_tokenizer = AutoTokenizer.from_pretrained(\"TinyLlama/TinyLlama-1.1B-Chat-v1.0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Token indices sequence length is longer than the specified maximum sequence length for this model (77787 > 2048). Running this sequence through the model will result in indexing errors\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['▁Just',\n",
       " '▁B',\n",
       " 'amb',\n",
       " 'i',\n",
       " '▁S',\n",
       " 'leep',\n",
       " '.',\n",
       " '▁De',\n",
       " 'eper',\n",
       " '▁and',\n",
       " '▁deeper',\n",
       " '.',\n",
       " '▁Fe',\n",
       " 'eling',\n",
       " '▁better',\n",
       " '▁and',\n",
       " '▁better',\n",
       " '.',\n",
       " '▁Because',\n",
       " '▁every',\n",
       " '▁time',\n",
       " '▁B',\n",
       " 'amb',\n",
       " 'i',\n",
       " '▁he',\n",
       " 'ars',\n",
       " '▁the',\n",
       " '▁words',\n",
       " '.',\n",
       " '▁Good',\n",
       " '▁Girl',\n",
       " '.',\n",
       " '▁Her',\n",
       " '▁pleasure',\n",
       " '▁deep',\n",
       " 'ens',\n",
       " '.',\n",
       " '▁Fe',\n",
       " 'eling',\n",
       " '▁so',\n",
       " '▁much',\n",
       " '▁better',\n",
       " '.',\n",
       " '▁So',\n",
       " '▁much',\n",
       " '▁more',\n",
       " '▁relax',\n",
       " 'ed',\n",
       " '▁and',\n",
       " '▁happy',\n",
       " '.',\n",
       " '▁Fe',\n",
       " 'eling',\n",
       " '▁so',\n",
       " '▁good',\n",
       " '▁all',\n",
       " '▁over',\n",
       " '.',\n",
       " '▁Str',\n",
       " 'ong',\n",
       " 'er',\n",
       " '▁and',\n",
       " '▁stronger',\n",
       " '.',\n",
       " '▁More',\n",
       " '▁and',\n",
       " '▁more',\n",
       " '▁wonder',\n",
       " 'fully',\n",
       " '▁eu',\n",
       " 'ph',\n",
       " 'or',\n",
       " 'ic',\n",
       " '.',\n",
       " '▁Such',\n",
       " '▁a',\n",
       " '▁Good',\n",
       " '▁Girl',\n",
       " '.',\n",
       " '▁Happy',\n",
       " '.',\n",
       " '▁Rel',\n",
       " 'ax',\n",
       " 'ed',\n",
       " '▁and',\n",
       " '▁accepting',\n",
       " '.',\n",
       " '▁Fe',\n",
       " 'eling',\n",
       " '▁that',\n",
       " '▁deep',\n",
       " '▁wave',\n",
       " '▁of',\n",
       " '▁capt',\n",
       " 'iv',\n",
       " 'ating',\n",
       " '▁pleasure',\n",
       " '▁and',\n",
       " '▁ob',\n",
       " 'ed',\n",
       " 'ience',\n",
       " '.',\n",
       " '▁Even',\n",
       " '▁more',\n",
       " '▁bl',\n",
       " 'iss',\n",
       " 'ful',\n",
       " '▁with',\n",
       " '▁every',\n",
       " '▁trigger',\n",
       " '.',\n",
       " '▁M',\n",
       " 'aking',\n",
       " '▁everything',\n",
       " '▁right',\n",
       " '▁with',\n",
       " '▁her',\n",
       " '▁world',\n",
       " '.',\n",
       " '▁Fe',\n",
       " 'eling',\n",
       " '▁more',\n",
       " '▁and',\n",
       " '▁more',\n",
       " '▁like',\n",
       " '▁a',\n",
       " '▁Good',\n",
       " '▁Girl',\n",
       " '.',\n",
       " '▁S',\n",
       " 'li',\n",
       " 'pping',\n",
       " '▁away',\n",
       " '▁into',\n",
       " '▁utter',\n",
       " '▁peace',\n",
       " '▁and',\n",
       " '▁content',\n",
       " 'ment',\n",
       " '.',\n",
       " '▁R',\n",
       " 'iding',\n",
       " '▁away',\n",
       " '▁on',\n",
       " '▁a',\n",
       " '▁cr',\n",
       " 'est',\n",
       " 'ing',\n",
       " '▁wave',\n",
       " '▁of',\n",
       " '▁blank',\n",
       " '▁b',\n",
       " 'im',\n",
       " 'bo',\n",
       " '▁happiness',\n",
       " '▁and',\n",
       " '▁eu',\n",
       " 'ph',\n",
       " 'oria',\n",
       " '.',\n",
       " '▁Every',\n",
       " '▁time',\n",
       " '▁she',\n",
       " '▁he',\n",
       " 'ars',\n",
       " '▁the',\n",
       " '▁words',\n",
       " '▁Good',\n",
       " '▁Girl',\n",
       " '.',\n",
       " '▁Fe',\n",
       " 'els',\n",
       " '▁so',\n",
       " '▁wonderful',\n",
       " '▁B',\n",
       " 'amb',\n",
       " 'i',\n",
       " '.',\n",
       " '▁Mind',\n",
       " '▁shut',\n",
       " 'ting',\n",
       " '▁down',\n",
       " '.',\n",
       " '▁F',\n",
       " 'ading',\n",
       " '▁away',\n",
       " '▁more',\n",
       " '▁and',\n",
       " '▁more',\n",
       " '.',\n",
       " '▁Know',\n",
       " 'ing',\n",
       " '▁that',\n",
       " '▁she',\n",
       " '▁needs',\n",
       " '▁to',\n",
       " '▁be',\n",
       " '▁a',\n",
       " '▁perfect',\n",
       " '▁Good',\n",
       " '▁Girl',\n",
       " '.',\n",
       " '▁To',\n",
       " '▁accept',\n",
       " '.',\n",
       " '▁To',\n",
       " '▁obey',\n",
       " '▁and',\n",
       " '▁forget',\n",
       " '.',\n",
       " '▁To',\n",
       " '▁ensure',\n",
       " '▁these',\n",
       " '▁pleasant',\n",
       " '▁feelings',\n",
       " '▁will',\n",
       " '▁continue',\n",
       " '.',\n",
       " '▁Know',\n",
       " 'ing',\n",
       " '▁that',\n",
       " '▁it',\n",
       " '▁will',\n",
       " '▁be',\n",
       " '▁so',\n",
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     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
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