Delete .ipynb_checkpoints
Browse files
.ipynb_checkpoints/Hugging_Face_Upload_Download_V16-checkpoint.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "0abc7dd7",
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"metadata": {},
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"source": [
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"### Master Notebook for Hugging Face repos Upload and Download V16\n",
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"\n",
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"### Always get latest version before starting to use : https://www.patreon.com/posts/104672510\n",
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"\n",
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"### Execute below cell once to install libraries\n",
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"\n",
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"### Don't forget to set accurate folder and file paths and repo names befor executing cells"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "caa74bef",
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install huggingface_hub --upgrade\n",
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"\n",
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"!pip install ipywidgets --upgrade\n",
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"\n",
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"!pip install hf_transfer --upgrade\n",
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"\n",
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"!pip install hf_xet --upgrade\n",
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"\n",
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"!pip install --upgrade jupyterlab-widgets\n",
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"\n",
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"!pip install --upgrade ipywidgets\n",
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"\n",
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"!jupyter nbextension enable --py widgetsnbextension"
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]
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},
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{
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"cell_type": "markdown",
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"id": "502249bf",
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"metadata": {},
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"source": [
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"### Use below cell to paste your Hugging Face token key. \n",
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"\n",
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"### Access Tokens are here : https://huggingface.co/settings/tokens"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0d8027c8",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import subprocess\n",
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"import platform\n",
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"\n",
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"hugging_face_token = 'replace_with_your_HF_Token'\n",
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"\n",
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"# Set the environment variable\n",
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"os.environ['HUGGING_FACE_HUB_TOKEN'] = hugging_face_token\n",
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"os.environ['HF_HUB_ENABLE_HF_TRANSFER'] = \"1\"\n",
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"os.environ['HF_HUB_VERBOSITY'] = \"debug\"\n",
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"\n",
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"\n",
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"# Determine the operating system\n",
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"system = platform.system()\n",
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"\n",
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"if system == \"Linux\":\n",
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" export_command = f'export HUGGING_FACE_HUB_TOKEN={hugging_face_token}'\n",
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" subprocess.run(export_command, shell=True, check=True)\n",
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" export_command = f'export HF_HUB_ENABLE_HF_TRANSFER=1'\n",
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" subprocess.run(export_command, shell=True, check=True) \n",
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" export_command = f'export HF_HUB_VERBOSITY=\"debug\"'\n",
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" subprocess.run(export_command, shell=True, check=True) \n",
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"elif system == \"Windows\":\n",
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" set_command = f'set HUGGING_FACE_HUB_TOKEN={hugging_face_token}'\n",
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" subprocess.run(set_command, shell=True, check=True)\n",
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" export_command = f'set HF_HUB_ENABLE_HF_TRANSFER=1'\n",
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" subprocess.run(export_command, shell=True, check=True) \n",
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" export_command = f'set HF_HUB_VERBOSITY=\"debug\"'\n",
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" subprocess.run(export_command, shell=True, check=True) \n",
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"\n",
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"# Command to log in using the token\n",
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"login_command = ['huggingface-cli', 'login', '--token', hugging_face_token]\n",
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"\n",
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"# Execute the login command and capture output\n",
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"try:\n",
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" result = subprocess.run(login_command, check=True, capture_output=True, text=True)\n",
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" print(\"Output:\", result.stdout)\n",
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" print(\"Error:\", result.stderr)\n",
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"except subprocess.CalledProcessError as e:\n",
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" print(\"Command failed with exit code:\", e.returncode)\n",
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" print(\"Output:\", e.output)\n",
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" print(\"Error:\", e.stderr)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "01529333-a7c2-4e13-bfc9-ebf053691051",
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"metadata": {},
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"source": [
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"### Very fast new upload - Wait till UPLOAD COMPLETED printed"
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]
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},
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{
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"cell_type": "raw",
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"id": "85bd218b-d08f-46b7-8c19-953ccc019bf6",
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"metadata": {},
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"source": [
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"INFO : On Windows give the path like this E:\\\\MMAudio_v9 - use double \\\\"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "30b96a4f",
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"metadata": {},
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"outputs": [],
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"source": [
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"!huggingface-cli upload-large-folder \"YourUserName/reponame\" \"/home/Ubuntu/apps/StableSwarmUI/Models/diffusion_models\" --repo-type=model --no-bars\n",
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"\n",
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"print(\".\\n.\\nUPLOAD COMPLETED\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4e7a6316",
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"metadata": {},
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"source": [
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"### Recommended - Very fast new upload V2 - Wait till UPLOAD COMPLETED printed"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "75a18901",
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"metadata": {},
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"outputs": [],
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"source": [
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"from huggingface_hub import HfApi\n",
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"\n",
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"api = HfApi()\n",
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"\n",
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"api.upload_large_folder(repo_id=\"YourUserName/reponame\", \n",
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" repo_type=\"model\", \n",
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" folder_path=r\"/home/Ubuntu/apps/StableSwarmUI/Models/diffusion_models\")\n",
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"\n",
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"print(\".\\n.\\nUPLOAD COMPLETED\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "58da07da-2e0b-4a32-a36d-ddf511800c58",
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"metadata": {},
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"source": [
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"### Upload a single file with specific name to remote repo - Wait till UPLOAD COMPLETED printed"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0502703b-8b44-4e58-af2c-82f67d713548",
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"metadata": {},
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"outputs": [],
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"source": [
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"# This cell is used to upload single file into a repo with certain name\n",
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"\n",
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"from huggingface_hub import HfApi\n",
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"api = HfApi()\n",
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"api.upload_file(\n",
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" path_or_fileobj=r\"/home/Ubuntu/apps/stable-diffusion-webui/models/Stable-diffusion/model_name.safetensors\",\n",
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" path_in_repo=\"model_name.safetensors\",\n",
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" repo_id=\"YourUserName/reponame\",\n",
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" repo_type=\"model\",\n",
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")\n",
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"\n",
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"print(\".\\n.\\nUPLOAD COMPLETED\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "7381726f",
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"metadata": {},
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"source": [
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"### To download all files in given Hugging Face repository use below - Wait till DOWNLOAD COMPLETED printed"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "90f6c9b1",
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"metadata": {},
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"outputs": [],
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"source": [
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"# You can run this cell multiple times if any error occurs it will resume\n",
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"\n",
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"from huggingface_hub import snapshot_download\n",
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"import os\n",
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"\n",
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"# Ensure the local directory exists\n",
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"\n",
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"\n",
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"repo_id=\"YourUserName/reponame\"\n",
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"local_dir = \"/home/Ubuntu/apps/StableSwarmUI/Models/diffusion_models\"\n",
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"\n",
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"os.makedirs(local_dir, exist_ok=True)\n",
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"\n",
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"snapshot_download(repo_id=repo_id,local_dir=local_dir)\n",
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"\n",
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"print(\".\\n.\\nDOWNLOAD COMPLETED\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "09f0f192-4d6b-4511-8366-6c676cd2404c",
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"metadata": {},
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"source": [
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"### Download a specific sub directory / folder - Wait till DOWNLOAD COMPLETED printed"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "download_subdirectory",
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"metadata": {},
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"outputs": [],
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"source": [
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"# This cell downloads a specific subdirectory from a given repo\n",
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"\n",
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"from huggingface_hub import snapshot_download\n",
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"import os\n",
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"\n",
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"# Define the repository and subdirectory\n",
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"repo_id = \"YourUserName/reponame\"\n",
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"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",
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"local_dir = \"/home/Ubuntu/apps/StableSwarmUI/Models/diffusion_models\"\n",
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"\n",
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"# Ensure the local directory exists\n",
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"os.makedirs(local_dir, exist_ok=True)\n",
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"\n",
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"# Download only the specific subdirectory\n",
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"snapshot_download(\n",
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" repo_id=repo_id,\n",
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" local_dir=local_dir,\n",
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" allow_patterns=subdirectory\n",
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")\n",
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"\n",
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"print(f\"Downloaded {subdirectory} from {repo_id} to {local_dir}\")\n",
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"print(\".\\n.\\nDOWNLOAD COMPLETED\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "47b04ce9-9653-4e4f-9bd9-1b6ed383f502",
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"metadata": {},
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"source": [
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"### Download a specific files - Ultra Blazing Fast Download"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "download_specific_file",
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"metadata": {},
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"outputs": [],
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"source": [
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"# This cell downloads a specific files from a given repo\n",
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"# You can download 1 or more specific files ultra fast\n",
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"# Wait until you see DOWNLOAD COMPLETED - status not shown on RunPod proxy\n",
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"\n",
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"from huggingface_hub import snapshot_download\n",
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"import os\n",
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"\n",
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"# Define the repository, file path, and local directory\n",
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"repo_id_set = \"YourUserName/reponame\"\n",
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"local_dir_set = f\"/home/Ubuntu/apps/StableSwarmUI/Models/diffusion_models\"\n",
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"\n",
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"# Ensure the local directory exists\n",
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"os.makedirs(local_dir_set, exist_ok=True)\n",
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"print(\".\\n.\\nDOWNLOAD Started...\")\n",
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"snapshot_download(\n",
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" repo_id=repo_id_set,\n",
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" allow_patterns=[\"1024_no_caption-000060.safetensors\", \"1024_with_caption.safetensors\",\"file3.zip\"],\n",
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" local_dir=local_dir_set,\n",
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" )\n",
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"\n",
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"print(\".\\n.\\nDOWNLOAD COMPLETED\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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