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{
"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"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|