Fooocus/fooocus_colab.ipynb
uptotec 0895a6ae44 feat: added a check for base model
added a check to make sure that the downloaded model is SDXL
2024-02-05 13:57:48 +02:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Run Fooocus"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "VjYy0F2gZIPR"
},
"outputs": [],
"source": [
"!pip install pygit2==1.12.2\n",
"%cd /content\n",
"!git clone https://github.com/lllyasviel/Fooocus.git\n",
"%cd /content/Fooocus\n",
"!python entry_with_update.py --share\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Download checkpoints and LoRAs from civitai\n",
"to download checkpoints and LoRAs from civitai you have to run Fooocus first\n",
"\n",
"https://civitai.com/models"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# put the link of the model you want to download (checkpoint or LoRA)\n",
"# link can specify a version id and if not specified the latest version will be downloaded\n",
"# url example without version id: https://civitai.com/models/133005/juggernaut-xl\n",
"# url example with version id: https://civitai.com/models/133005?modelVersionId=252902\n",
"\n",
"civitai_url = \"https://civitai.com/models/133005/juggernaut-xl\"\n",
"\n",
"# -----------------------------\n",
"import requests\n",
"from urllib.parse import urlparse\n",
"from urllib.parse import parse_qs\n",
"\n",
"allowed_types = ['Checkpoint', 'LORA']\n",
"save_locations = {\n",
" 'Checkpoint': '/content/Fooocus/models/checkpoints',\n",
" 'LORA': '/content/Fooocus/models/loras'\n",
"}\n",
"\n",
"parsed_url = urlparse(civitai_url)\n",
"\n",
"model_id = parsed_url.path.split('/')[parsed_url.path.split('/').index('models') + 1]\n",
"model_version_id = parse_qs(parsed_url.query).get('modelVersionId')\n",
"\n",
"url = \"https://civitai.com/api/v1/models/\" + model_id\n",
"response = requests.get(url)\n",
"\n",
"if response.status_code != 200:\n",
" raise RuntimeError('model not found')\n",
"\n",
"data = response.json()\n",
"model_type = data.get('type')\n",
"\n",
"if model_type not in allowed_types:\n",
" raise RuntimeError('model is not a checkpoint or LoRA')\n",
"\n",
"model_versions = data.get('modelVersions')\n",
"\n",
"selected_version = None\n",
"\n",
"if model_version_id:\n",
" for model_version in model_versions:\n",
" if str(model_version.get('id')) == model_version_id[0]:\n",
" selected_version = model_version\n",
"else:\n",
" selected_version = model_versions[0]\n",
"\n",
"if selected_version is None:\n",
" raise RuntimeError(\"this version doesn't exist\")\n",
"\n",
"if \"SDXL\" not in selected_version.get('baseModel'):\n",
" raise RuntimeError(\"this model is not SDXL\")\n",
"\n",
"files = selected_version.get('files')\n",
"primary_file = None\n",
"\n",
"for f in files:\n",
" if f.get('primary'):\n",
" primary_file = f\n",
"\n",
"download_url = primary_file.get('downloadUrl')\n",
"file_name = primary_file.get('name')\n",
"\n",
"LOCATION = save_locations[model_type]\n",
"%cd $LOCATION\n",
"\n",
"model_name = data.get('name')\n",
"selected_version_name = selected_version.get('name')\n",
"print(f'downloading {model_name} ({model_type} version {selected_version_name})')\n",
"\n",
"get_ipython().system(f'wget -O \"{file_name}\" \"{download_url}\"')"
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"gpuType": "T4",
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
}