{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3cb8b683-840f-4981-af83-018f067c5c94",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Collecting transformers\n",
      "  Downloading transformers-4.47.0-py3-none-any.whl (10.1 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.1/10.1 MB\u001b[0m \u001b[31m59.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m0:01\u001b[0m\n",
      "\u001b[?25hCollecting huggingface-hub<1.0,>=0.24.0\n",
      "  Downloading huggingface_hub-0.27.0-py3-none-any.whl (450 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m450.5/450.5 KB\u001b[0m \u001b[31m36.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hCollecting tqdm>=4.27\n",
      "  Downloading tqdm-4.67.1-py3-none-any.whl (78 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m78.5/78.5 KB\u001b[0m \u001b[31m12.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/lib/python3/dist-packages (from transformers) (1.21.5)\n",
      "Requirement already satisfied: filelock in /usr/lib/python3/dist-packages (from transformers) (3.6.0)\n",
      "Requirement already satisfied: packaging>=20.0 in /usr/lib/python3/dist-packages (from transformers) (21.3)\n",
      "Collecting safetensors>=0.4.1\n",
      "  Downloading safetensors-0.4.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (435 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m435.0/435.0 KB\u001b[0m \u001b[31m49.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hCollecting tokenizers<0.22,>=0.21\n",
      "  Downloading tokenizers-0.21.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.0 MB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.0/3.0 MB\u001b[0m \u001b[31m71.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m\n",
      "\u001b[?25hCollecting regex!=2019.12.17\n",
      "  Downloading regex-2024.11.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (781 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m781.7/781.7 KB\u001b[0m \u001b[31m59.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: requests in /usr/lib/python3/dist-packages (from transformers) (2.25.1)\n",
      "Requirement already satisfied: pyyaml>=5.1 in /usr/lib/python3/dist-packages (from transformers) (5.4.1)\n",
      "Requirement already satisfied: fsspec>=2023.5.0 in /usr/lib/python3/dist-packages (from huggingface-hub<1.0,>=0.24.0->transformers) (2024.3.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/lib/python3/dist-packages (from huggingface-hub<1.0,>=0.24.0->transformers) (4.9.0)\n",
      "Installing collected packages: tqdm, safetensors, regex, huggingface-hub, tokenizers, transformers\n",
      "Successfully installed huggingface-hub-0.27.0 regex-2024.11.6 safetensors-0.4.5 tokenizers-0.21.0 tqdm-4.67.1 transformers-4.47.0\n"
     ]
    }
   ],
   "source": [
    "!pip install transformers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e3672a9c-c8ab-4d13-9498-5450ca3d95c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "README.md\t\t\t  model-00002-of-00004.safetensors\n",
      "Untitled.ipynb\t\t\t  model-00003-of-00004.safetensors\n",
      "Untitled1.ipynb\t\t\t  model-00004-of-00004.safetensors\n",
      "added_tokens.json\t\t  model.safetensors.index.json\n",
      "checkpoint-120\t\t\t  pytorch_model-00001-of-00002.bin\n",
      "checkpoint-40\t\t\t  pytorch_model-00002-of-00002.bin\n",
      "checkpoint-80\t\t\t  pytorch_model.bin.index.json\n",
      "checkpoint-90\t\t\t  special_tokens_map.json\n",
      "config.json\t\t\t  tokenizer.json\n",
      "generation_config.json\t\t  tokenizer_config.json\n",
      "merges.txt\t\t\t  training_args.bin\n",
      "model-00001-of-00004.safetensors  vocab.json\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4a7a57e8-6bc3-4d15-88ac-942e8347b7cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading checkpoint shards: 100%|██████████| 4/4 [00:20<00:00,  5.04s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model and tokenizer loaded successfully!\n"
     ]
    }
   ],
   "source": [
    "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
    "\n",
    "# Path to your local checkpoint directory\n",
    "checkpoint_path = \"checkpoint-162\"\n",
    "\n",
    "# Load the model and tokenizer\n",
    "model = AutoModelForCausalLM.from_pretrained(checkpoint_path)\n",
    "tokenizer = AutoTokenizer.from_pretrained(checkpoint_path)\n",
    "\n",
    "# Verify loading\n",
    "print(\"Model and tokenizer loaded successfully!\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c3b9fcde-a4f3-4217-ba9a-cf799800cd63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RepoUrl('https://huggingface.co/neginashz/checkpoint-162', endpoint='https://huggingface.co', repo_type='model', repo_id='neginashz/checkpoint-162')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from huggingface_hub import create_repo\n",
    "\n",
    "create_repo(repo_id=\"neginashz/checkpoint-162\", private=False, exist_ok=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6e19721a-b69c-42e6-a740-04e4b8ded4fa",
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_9719/2177510705.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"neginashz/checkpoint-162\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mtokenizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"neginashz/checkpoint-162\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.10/site-packages/transformers/modeling_utils.py\u001b[0m in \u001b[0;36mpush_to_hub\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   3085\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mtags\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3086\u001b[0m             \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"tags\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtags\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3087\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3088\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3089\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget_memory_footprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreturn_buffers\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.10/site-packages/transformers/utils/hub.py\u001b[0m in \u001b[0;36mpush_to_hub\u001b[0;34m(self, repo_id, use_temp_dir, commit_message, private, token, max_shard_size, create_pr, safe_serialization, revision, commit_description, tags, **deprecated_kwargs)\u001b[0m\n\u001b[1;32m    947\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    948\u001b[0m             \u001b[0;31m# Save all files.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 949\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwork_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmax_shard_size\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmax_shard_size\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msafe_serialization\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msafe_serialization\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    950\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    951\u001b[0m             \u001b[0;31m# Update model card if needed:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.10/site-packages/transformers/modeling_utils.py\u001b[0m in \u001b[0;36msave_pretrained\u001b[0;34m(self, save_directory, is_main_process, state_dict, save_function, push_to_hub, max_shard_size, safe_serialization, variant, token, save_peft_format, **kwargs)\u001b[0m\n\u001b[1;32m   3032\u001b[0m                 \u001b[0;31m# At some point we will need to deal better with save_function (used for TPU and other distributed\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3033\u001b[0m                 \u001b[0;31m# joyfulness), but for now this enough.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3034\u001b[0;31m                 \u001b[0msafe_save_file\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mshard\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msave_directory\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshard_file\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetadata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m\"format\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m\"pt\"\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3035\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3036\u001b[0m                 \u001b[0msave_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mshard\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msave_directory\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mshard_file\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.10/site-packages/safetensors/torch.py\u001b[0m in \u001b[0;36msave_file\u001b[0;34m(tensors, filename, metadata)\u001b[0m\n\u001b[1;32m    284\u001b[0m     \u001b[0;31m`\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    285\u001b[0m     \"\"\"\n\u001b[0;32m--> 286\u001b[0;31m     \u001b[0mserialize_file\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_flatten\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtensors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetadata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmetadata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    287\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    288\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "model.push_to_hub(\"neginashz/checkpoint-162\")\n",
    "tokenizer.push_to_hub(\"neginashz/checkpoint-162\")\n"
   ]
  }
 ],
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