{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7208d1dc-06eb-457e-bcf1-fb0d6cc4d39e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "with zipfile.ZipFile('training_args.bin', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./unzipped_content')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6acc7c33-58c2-41af-a2ed-479b77dde45e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.TrainingArguments object at 0x7f20c437c8b0>\n"
     ]
    }
   ],
   "source": [
    "import pickle\n",
    "class TrainingArguments:\n",
    "    pass\n",
    "with open('./unzipped_content/training_args/data.pkl', 'rb') as f:\n",
    "    data = pickle.load(f)\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "59e6f842-4e9f-497b-a2ae-6c972782aabb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
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   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
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 "nbformat": 4,
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}