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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [
{
"file_id": "https://gist.github.com/AdamOswald/70f8e6429e99ff44799a7c51b4517496#file-copy-of-fine-tuned-diffusion-gradio-ipynb",
"timestamp": 1675347363746,
}
]
},
"kernelspec": {"name": "python3", "display_name": "Python 3"},
"language_info": {"name": "python"},
"gpuClass": "standard",
"accelerator": "GPU",
},
"cells": [
{
"cell_type": "markdown",
"source": [
"**Finetuned Diffusion demo 🪄🖼️** \n",
"\n",
"With this app you can run multiple fine-tuned Stable Diffusion models, trained on different styles: [Arcane](https://huggingface.co/nitrosocke/Arcane-Diffusion), [Archer](https://huggingface.co/nitrosocke/archer-diffusion), [Elden Ring](https://huggingface.co/nitrosocke/elden-ring-diffusion), [Spider-Verse](https://huggingface.co/nitrosocke/spider-verse-diffusion), [Modern Disney](https://huggingface.co/nitrosocke/modern-disney-diffusion), [Classic Disney](https://huggingface.co/nitrosocke/classic-anim-diffusion), [Waifu](https://huggingface.co/hakurei/waifu-diffusion), [Pokémon](https://huggingface.co/lambdalabs/sd-pokemon-diffusers), [Pony Diffusion](https://huggingface.co/AstraliteHeart/pony-diffusion), [Robo Diffusion](https://huggingface.co/nousr/robo-diffusion), [Cyberpunk Anime](https://huggingface.co/DGSpitzer/Cyberpunk-Anime-Diffusion), [Tron Legacy](https://huggingface.co/dallinmackay/Tron-Legacy-diffusion) + any other custom Diffusers 🧨 SD model hosted on HuggingFace 🤗.",
],
"metadata": {"id": "oBB6SkL2REFn"},
},
{
"cell_type": "markdown",
"source": ["### 1. Install dependencies"],
"metadata": {"id": "2o-2jPqITvtD"},
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "8WYSV-73rslm",
"executionInfo": {
"status": "ok",
"timestamp": 1675347315623,
"user_tz": 300,
"elapsed": 320217,
"user": {"displayName": "", "userId": ""},
},
"outputId": "0d67fb80-8d83-4819-a2ff-bc7458c794ac",
"colab": {"base_uri": "https://localhost:8080/"},
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cloning into 'finetuned_diffusionl'...\n",
"remote: Enumerating objects: 24, done.\u001b[K\n",
"remote: Counting objects: 100% (15/15), done.\u001b[K\n",
"remote: Compressing objects: 100% (15/15), done.\u001b[K\n",
"remote: Total 24 (delta 7), reused 0 (delta 0), pack-reused 9\u001b[K\n",
"Unpacking objects: 100% (24/24), 95.73 KiB | 2.90 MiB/s, done.\n",
"/content/finetuned_diffusionl\n",
"Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/, https://download.pytorch.org/whl/cu113\n",
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" Cloning https://github.com/huggingface/diffusers.git to /tmp/pip-req-build-b28tkofz\n",
" Running command git clone --filter=blob:none --quiet https://github.com/huggingface/diffusers.git /tmp/pip-req-build-b28tkofz\n",
" Resolved https://github.com/huggingface/diffusers.git to commit 68ef0666e22a66a5ae6cb57104a8213e85b4be38\n",
" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
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" Running command git clone --filter=blob:none --quiet https://github.com/huggingface/transformers /tmp/pip-req-build-gpkpb3qw\n",
" Resolved https://github.com/huggingface/transformers to commit db572b38541269f3653f0cbeca58520ed18ff80c\n",
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],
}
],
"source": [
"!git clone https://huggingface.co/spaces/AdamOswald1/finetuned_diffusionl\n",
"%cd finetuned_diffusionl/\n",
"!pip install -r requirements.txt\n",
"!pip install gradio==3.17.1\n",
"\n",
"!pip uninstall -y xformers\n",
"!pip install -q https://github.com/camenduru/stable-diffusion-webui-colab/releases/download/0.0.15/xformers-0.0.15.dev0+1515f77.d20221130-cp38-cp38-linux_x86_64.whl",
],
},
{
"cell_type": "markdown",
"source": [
"### 2. Run\n",
"\n",
"Expand this cell and run it. After it finishes loading, **open the generated gradio public link** (e.g. https://xxxx.gradio.app) in the output.\n",
"\n",
"When running in a colab, models need to be downloaded the first time you use them, so give it some time.",
],
"metadata": {"id": "g51-cBLlTsO4"},
},
{
"cell_type": "code",
"source": ["!python app.py"],
"metadata": {"id": "dMhWUqKdNzn3"},
"execution_count": null,
"outputs": [],
},
],
}
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