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{
"cells": [
{
"cell_type": "markdown",
"id": "0abc7dd7",
"metadata": {},
"source": [
"### Master Notebook for Hugging Face repos Upload and Download V11\n",
"\n",
"### Always get latest version before starting to use : https://www.patreon.com/posts/104672510\n",
"\n",
"### Execute below cell once to install libraries\n",
"\n",
"### Don't forget to set accurate folder and file paths and repo names befor executing cells"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "caa74bef",
"metadata": {},
"outputs": [],
"source": [
"!pip install huggingface_hub --upgrade\n",
"\n",
"!pip install ipywidgets --upgrade\n",
"\n",
"!pip install git+https://github.com/huggingface/huggingface_hub --upgrade\n",
"\n",
"!pip install hf_transfer --upgrade\n",
"\n",
"!pip install --upgrade jupyterlab-widgets\n",
"!pip install --upgrade ipywidgets\n",
"!jupyter nbextension enable --py widgetsnbextension"
]
},
{
"cell_type": "markdown",
"id": "502249bf",
"metadata": {},
"source": [
"### Use below cell to paste your Hugging Face token key. \n",
"\n",
"### Access Tokens are here : https://huggingface.co/settings/tokens"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0d8027c8",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import subprocess\n",
"import platform\n",
"\n",
"hugging_face_token = 'TOKEN'\n",
"\n",
"# Set the environment variable\n",
"os.environ['HUGGING_FACE_HUB_TOKEN'] = hugging_face_token\n",
"os.environ['HF_HUB_ENABLE_HF_TRANSFER'] = \"1\"\n",
"os.environ['HF_HUB_VERBOSITY'] = \"debug\"\n",
"\n",
"\n",
"# Determine the operating system\n",
"system = platform.system()\n",
"\n",
"if system == \"Linux\":\n",
" export_command = f'export HUGGING_FACE_HUB_TOKEN={hugging_face_token}'\n",
" subprocess.run(export_command, shell=True, check=True)\n",
" export_command = f'export HF_HUB_ENABLE_HF_TRANSFER=1'\n",
" subprocess.run(export_command, shell=True, check=True) \n",
" export_command = f'export HF_HUB_VERBOSITY=\"debug\"'\n",
" subprocess.run(export_command, shell=True, check=True) \n",
"elif system == \"Windows\":\n",
" set_command = f'set HUGGING_FACE_HUB_TOKEN={hugging_face_token}'\n",
" subprocess.run(set_command, shell=True, check=True)\n",
" export_command = f'set HF_HUB_ENABLE_HF_TRANSFER=1'\n",
" subprocess.run(export_command, shell=True, check=True) \n",
" export_command = f'set HF_HUB_VERBOSITY=\"debug\"'\n",
" subprocess.run(export_command, shell=True, check=True) \n",
"\n",
"# Command to log in using the token\n",
"login_command = ['huggingface-cli', 'login', '--token', hugging_face_token]\n",
"\n",
"# Execute the login command and capture output\n",
"try:\n",
" result = subprocess.run(login_command, check=True, capture_output=True, text=True)\n",
" print(\"Output:\", result.stdout)\n",
" print(\"Error:\", result.stderr)\n",
"except subprocess.CalledProcessError as e:\n",
" print(\"Command failed with exit code:\", e.returncode)\n",
" print(\"Output:\", e.output)\n",
" print(\"Error:\", e.stderr)"
]
},
{
"cell_type": "markdown",
"id": "afb149da",
"metadata": {},
"source": [
"### Very fast new upload - Wait till UPLOAD COMPLETED printed"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "30b96a4f",
"metadata": {},
"outputs": [],
"source": [
"!huggingface-cli upload-large-folder \"YourUserName/reponame\" r\"/home/Ubuntu/apps/StableSwarmUI/Models/Lora\" --repo-type=model --no-bars\n",
"\n",
"print(\".\\n.\\nUPLOAD COMPLETED\")"
]
},
{
"cell_type": "markdown",
"id": "4e7a6316",
"metadata": {},
"source": [
"### Very fast new upload V2 - Wait till UPLOAD COMPLETED printed"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "75a18901",
"metadata": {},
"outputs": [],
"source": [
"from huggingface_hub import HfApi\n",
"\n",
"# Initialize the HfApi instance\n",
"api = HfApi()\n",
"\n",
"# Define the repo_id and the local folder to upload\n",
"repo_id = \"rexlapix/amy\" # Your Hugging Face repo\n",
"folder_path = r\"/home/Ubuntu/Desktop/workspace/test\" # Path to your local folder\n",
"\n",
"# Upload the folder to the specific subdirectory in the repo\n",
"api.upload_large_folder(\n",
" repo_id=repo_id, \n",
" repo_type=\"model\", \n",
" folder_path=folder_path, \n",
" path_in_repo=\"amy_FLUX-FT/model_fp16\" # Target directory inside the repo\n",
")\n",
"\n",
"print(\"\\nUPLOAD COMPLETED\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "999f28d5",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"from huggingface_hub import HfApi\n",
"\n",
"# Initialize the API\n",
"api = HfApi()\n",
"\n",
"# Define the local file path\n",
"local_file_path = r\"/home/Ubuntu/Desktop/workspace/cooked/amy_FLUX-FT/ml/model_fp8/amy_flux_fp8-000200.safetensors\"\n",
"\n",
"# Automatically extract the default file name from the local path\n",
"default_file_name = os.path.basename(local_file_path)\n",
"\n",
"# Define the path in the repository using the extracted file name\n",
"path_in_repo = f\"amy_FLUX-FT/model_fp8/{default_file_name}\"\n",
"\n",
"# Upload the file\n",
"api.upload_file(\n",
" path_or_fileobj=local_file_path,\n",
" path_in_repo=path_in_repo,\n",
" repo_id=\"rexlapix/amy\",\n",
" repo_type=\"model\",\n",
")\n",
"\n",
"print(\".\\n.\\nUPLOAD COMPLETED\")\n"
]
},
{
"cell_type": "markdown",
"id": "58da07da-2e0b-4a32-a36d-ddf511800c58",
"metadata": {},
"source": [
"### Upload a single file with specific name to remote repo - Wait till UPLOAD COMPLETED printed"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0502703b-8b44-4e58-af2c-82f67d713548",
"metadata": {},
"outputs": [],
"source": [
"# This cell is used to upload single file into a repo with certain name\n",
"\n",
"from huggingface_hub import HfApi\n",
"api = HfApi()\n",
"api.upload_file(\n",
" path_or_fileobj=r\"/home/Ubuntu/apps/stable-diffusion-webui/models/Stable-diffusion/model_name.safetensors\",\n",
" path_in_repo=\"model_name.safetensors\",\n",
" repo_id=\"YourUserName/reponame\",\n",
" repo_type=\"model\",\n",
")\n",
"\n",
"print(\".\\n.\\nUPLOAD COMPLETED\")"
]
},
{
"cell_type": "markdown",
"id": "2dd50994-5595-46a6-b315-595ede0cf922",
"metadata": {},
"source": [
"### Upload a folder fast but not suggested for too big and many files - Wait till UPLOAD COMPLETED printed"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a89ece44-8f27-43bb-a7fc-e966409d6f5a",
"metadata": {},
"outputs": [],
"source": [
"# This cell is used to upload a folder into a repo with single commit\n",
"\n",
"from huggingface_hub import HfApi\n",
"api = HfApi()\n",
"api.upload_folder(\n",
" folder_path=r\"/home/Ubuntu/apps/stable-diffusion-webui/models/Stable-diffusion\",\n",
" repo_id=\"YourUserName/reponame\",\n",
" repo_type=\"model\",\n",
")\n",
"\n",
"print(\".\\n.\\nUPLOAD COMPLETED\")"
]
},
{
"cell_type": "markdown",
"id": "4d26f8d6-31cd-42a5-9477-ba1e77cd271c",
"metadata": {},
"source": [
"### To upload all files in given folder to the target Hugging Face repository use below - Wait till UPLOAD COMPLETED printed"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6fc96104",
"metadata": {},
"outputs": [],
"source": [
"# This cell uploads a folder into remote repo with multi commit\n",
"# Supports continue feature so if gets interrupted you can run again to continue / resume\n",
"\n",
"from huggingface_hub import HfApi\n",
"from huggingface_hub import get_collection, delete_collection_item\n",
"from huggingface_hub import upload_file\n",
"from huggingface_hub import (\n",
" HfFolder,\n",
" ModelCard,\n",
" ModelCardData,\n",
" create_repo,\n",
" hf_hub_download,\n",
" upload_folder,\n",
" whoami,\n",
")\n",
"api = HfApi()\n",
"upload_folder(\n",
" folder_path=r\"/home/Ubuntu/apps/stable-diffusion-webui/models/Stable-diffusion\",\n",
" repo_id=\"YourUserName/reponame\",\n",
" repo_type=\"model\",\n",
" multi_commits=True,\n",
" multi_commits_verbose=True,\n",
")\n",
"\n",
"print(\".\\n.\\nUPLOAD COMPLETED\")"
]
},
{
"cell_type": "markdown",
"id": "7381726f",
"metadata": {},
"source": [
"### To download all files in given Hugging Face repository use below - Wait till DOWNLOAD COMPLETED printed"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "90f6c9b1",
"metadata": {},
"outputs": [],
"source": [
"# You can run this cell multiple times if any error occurs it will resume\n",
"\n",
"from huggingface_hub import snapshot_download\n",
"import os\n",
"\n",
"# Ensure the local directory exists\n",
"\n",
"\n",
"repo_id=\"YourUserName/reponame\"\n",
"local_dir = \"/home/Ubuntu/apps/StableSwarmUI/Models/diffusion_models\"\n",
"\n",
"os.makedirs(local_dir, exist_ok=True)\n",
"\n",
"snapshot_download(repo_id=repo_id,local_dir=local_dir)\n",
"\n",
"print(\".\\n.\\nDOWNLOAD COMPLETED\")"
]
},
{
"cell_type": "markdown",
"id": "09f0f192-4d6b-4511-8366-6c676cd2404c",
"metadata": {},
"source": [
"### Download a specific sub directory / folder - Wait till DOWNLOAD COMPLETED printed"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "download_subdirectory",
"metadata": {},
"outputs": [],
"source": [
"# This cell downloads a specific subdirectory from a given repo\n",
"\n",
"from huggingface_hub import snapshot_download\n",
"import os\n",
"\n",
"# Define the repository and subdirectory\n",
"repo_id = \"YourUserName/reponame\"\n",
"subdirectory = \"folder_path_in_remote_repo/*\" # don't delete /* part just change folder path - if you get click to show javascript error ignore it and follow folder it will work\n",
"local_dir = \"/home/Ubuntu/apps/StableSwarmUI/Models/diffusion_models\"\n",
"\n",
"# Ensure the local directory exists\n",
"os.makedirs(local_dir, exist_ok=True)\n",
"\n",
"# Download only the specific subdirectory\n",
"snapshot_download(\n",
" repo_id=repo_id,\n",
" local_dir=local_dir,\n",
" allow_patterns=subdirectory\n",
")\n",
"\n",
"print(f\"Downloaded {subdirectory} from {repo_id} to {local_dir}\")\n",
"print(\".\\n.\\nDOWNLOAD COMPLETED\")"
]
},
{
"cell_type": "markdown",
"id": "47b04ce9-9653-4e4f-9bd9-1b6ed383f502",
"metadata": {},
"source": [
"### Download a specific files - Ultra Blazing Fast Download"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "download_specific_file",
"metadata": {},
"outputs": [],
"source": [
"# This cell downloads a specific files from a given repo\n",
"# You can download 1 or more specific files ultra fast\n",
"# Wait until you see DOWNLOAD COMPLETED - status not shown on RunPod proxy\n",
"\n",
"from huggingface_hub import snapshot_download\n",
"import os\n",
"\n",
"# Define the repository, file path, and local directory\n",
"repo_id_set = \"YourUserName/reponame\"\n",
"local_dir_set = f\"/home/Ubuntu/apps/StableSwarmUI/Models/diffusion_models\"\n",
"\n",
"# Ensure the local directory exists\n",
"os.makedirs(local_dir_set, exist_ok=True)\n",
"print(\".\\n.\\nDOWNLOAD Started...\")\n",
"snapshot_download(\n",
" repo_id=repo_id_set,\n",
" allow_patterns=[\"1024_no_caption-000060.safetensors\", \"1024_with_caption.safetensors\",\"file3.zip\"],\n",
" local_dir=local_dir_set,\n",
" )\n",
"\n",
"print(\".\\n.\\nDOWNLOAD COMPLETED\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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"nbformat": 4,
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