mirror of
https://github.com/sd-webui/stable-diffusion-webui.git
synced 2024-12-14 23:02:00 +03:00
444 lines
18 KiB
Plaintext
444 lines
18 KiB
Plaintext
{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"private_outputs": true,
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"provenance": [],
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"collapsed_sections": [
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"5-Bx4AsEoPU-",
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"xMWVQOg0G1Pj"
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]
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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},
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"accelerator": "GPU"
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},
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"[](https://colab.research.google.com/github/Sygil-Dev/sygil-webui/blob/dev/Web_based_UI_for_Stable_Diffusion_colab.ipynb)"
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],
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"metadata": {
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"id": "S5RoIM-5IPZJ"
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"# README"
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],
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"metadata": {
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"id": "5-Bx4AsEoPU-"
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"###<center>Web-based UI for Stable Diffusion</center>\n",
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"\n",
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"## Created by [Sygil-Dev](https://github.com/Sygil-Dev)\n",
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"\n",
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"## [Visit Sygil-Dev's Discord Server](https://discord.gg/gyXNe4NySY) [](https://discord.gg/gyXNe4NySY)\n",
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"\n",
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"## Installation instructions for:\n",
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"\n",
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"- **[Windows](https://sygil-dev.github.io/sygil-webui/docs/1.windows-installation.html)** \n",
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"- **[Linux](https://sygil-dev.github.io/sygil-webui/docs/2.linux-installation.html)**\n",
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"\n",
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"### Want to ask a question or request a feature?\n",
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"\n",
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"Come to our [Discord Server](https://discord.gg/gyXNe4NySY) or use [Discussions](https://github.com/Sygil-Dev/sygil-webui/discussions).\n",
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"\n",
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"## Documentation\n",
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"\n",
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"[Documentation is located here](https://sygil-dev.github.io/sygil-webui/)\n",
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"\n",
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"## Want to contribute?\n",
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"\n",
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"Check the [Contribution Guide](CONTRIBUTING.md)\n",
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"\n",
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"[Sygil-Dev](https://github.com/Sygil-Dev) main devs:\n",
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"\n",
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"*  [hlky](https://github.com/hlky)\n",
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"* [ZeroCool940711](https://github.com/ZeroCool940711)\n",
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"* [codedealer](https://github.com/codedealer)\n",
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"\n",
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"### Project Features:\n",
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"\n",
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"* Two great Web UI's to choose from: Streamlit or Gradio\n",
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"\n",
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"* No more manually typing parameters, now all you have to do is write your prompt and adjust sliders\n",
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"\n",
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"* Built-in image enhancers and upscalers, including GFPGAN and realESRGAN\n",
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"\n",
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"* Run additional upscaling models on CPU to save VRAM\n",
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"\n",
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"* Textual inversion 🔥: [info](https://textual-inversion.github.io/) - requires enabling, see [here](https://github.com/hlky/sd-enable-textual-inversion), script works as usual without it enabled\n",
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"\n",
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"* Advanced img2img editor with Mask and crop capabilities\n",
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"\n",
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"* Mask painting 🖌️: Powerful tool for re-generating only specific parts of an image you want to change (currently Gradio only)\n",
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"\n",
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"* More diffusion samplers 🔥🔥: A great collection of samplers to use, including:\n",
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" \n",
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" - `k_euler` (Default)\n",
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" - `k_lms`\n",
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" - `k_euler_a`\n",
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" - `k_dpm_2`\n",
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" - `k_dpm_2_a`\n",
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" - `k_heun`\n",
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" - `PLMS`\n",
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" - `DDIM`\n",
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"\n",
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"* Loopback ➿: Automatically feed the last generated sample back into img2img\n",
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"\n",
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"* Prompt Weighting 🏋️: Adjust the strength of different terms in your prompt\n",
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"\n",
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"* Selectable GPU usage with `--gpu <id>`\n",
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"\n",
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"* Memory Monitoring 🔥: Shows VRAM usage and generation time after outputting\n",
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"\n",
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"* Word Seeds 🔥: Use words instead of seed numbers\n",
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"\n",
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"* CFG: Classifier free guidance scale, a feature for fine-tuning your output\n",
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"\n",
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"* Automatic Launcher: Activate conda and run Stable Diffusion with a single command\n",
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"\n",
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"* Lighter on VRAM: 512x512 Text2Image & Image2Image tested working on 4GB\n",
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"\n",
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"* Prompt validation: If your prompt is too long, you will get a warning in the text output field\n",
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"\n",
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"* Copy-paste generation parameters: A text output provides generation parameters in an easy to copy-paste form for easy sharing.\n",
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"\n",
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"* Correct seeds for batches: If you use a seed of 1000 to generate two batches of two images each, four generated images will have seeds: `1000, 1001, 1002, 1003`.\n",
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"\n",
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"* Prompt matrix: Separate multiple prompts using the `|` character, and the system will produce an image for every combination of them.\n",
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"\n",
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"* Loopback for Image2Image: A checkbox for img2img allowing to automatically feed output image as input for the next batch. Equivalent to saving output image, and replacing input image with it.\n",
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"\n",
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"# Stable Diffusion Web UI\n",
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"\n",
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"A fully-integrated and easy way to work with Stable Diffusion right from a browser window.\n",
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"\n",
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"## Streamlit\n",
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"\n",
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"\n",
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"\n",
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"**Features:**\n",
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"\n",
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"- Clean UI with an easy to use design, with support for widescreen displays.\n",
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"- Dynamic live preview of your generations\n",
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"- Easily customizable presets right from the WebUI (Coming Soon!)\n",
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"- An integrated gallery to show the generations for a prompt or session (Coming soon!)\n",
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"- Better optimization VRAM usage optimization, less errors for bigger generations.\n",
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"- Text2Video - Generate video clips from text prompts right from the WEb UI (WIP)\n",
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"- Concepts Library - Run custom embeddings others have made via textual inversion.\n",
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"- Actively being developed with new features being added and planned - Stay Tuned!\n",
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"- Streamlit is now the new primary UI for the project moving forward.\n",
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"- *Currently in active development and still missing some of the features present in the Gradio Interface.*\n",
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"\n",
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"Please see the [Streamlit Documentation](docs/4.streamlit-interface.md) to learn more.\n",
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"\n",
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"## Gradio\n",
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"\n",
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"\n",
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"\n",
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"**Features:**\n",
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"\n",
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"- Older UI design that is fully functional and feature complete.\n",
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"- Has access to all upscaling models, including LSDR.\n",
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"- Dynamic prompt entry automatically changes your generation settings based on `--params` in a prompt.\n",
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"- Includes quick and easy ways to send generations to Image2Image or the Image Lab for upscaling.\n",
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"- *Note, the Gradio interface is no longer being actively developed and is only receiving bug fixes.*\n",
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"\n",
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"Please see the [Gradio Documentation](docs/5.gradio-interface.md) to learn more.\n",
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"\n",
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"## Image Upscalers\n",
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"\n",
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"---\n",
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"\n",
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"### GFPGAN\n",
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"\n",
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"\n",
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"\n",
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"Lets you improve faces in pictures using the GFPGAN model. There is a checkbox in every tab to use GFPGAN at 100%, and also a separate tab that just allows you to use GFPGAN on any picture, with a slider that controls how strong the effect is.\n",
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"\n",
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"If you want to use GFPGAN to improve generated faces, you need to install it separately.\n",
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"Download [GFPGANv1.4.pth](https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth) and put it\n",
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"into the `/sygil-webui/models/gfpgan` directory. \n",
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"\n",
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"### RealESRGAN\n",
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"\n",
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"\n",
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"\n",
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"Lets you double the resolution of generated images. There is a checkbox in every tab to use RealESRGAN, and you can choose between the regular upscaler and the anime version.\n",
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"There is also a separate tab for using RealESRGAN on any picture.\n",
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"\n",
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"Download [RealESRGAN_x4plus.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth) and [RealESRGAN_x4plus_anime_6B.pth](https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.2.4/RealESRGAN_x4plus_anime_6B.pth).\n",
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"Put them into the `stable-diffusion-webui/models/realesrgan` directory. \n",
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"\n",
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"\n",
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"\n",
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"### LSDR\n",
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"\n",
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"Download **LDSR** [project.yaml](https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1) and [model last.cpkt](https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1). Rename last.ckpt to model.ckpt and place both under `stable-diffusion-webui/models/ldsr/`\n",
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"\n",
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"### GoBig, and GoLatent *(Currently on the Gradio version Only)*\n",
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"\n",
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"More powerful upscalers that uses a seperate Latent Diffusion model to more cleanly upscale images.\n",
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"\n",
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"\n",
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"\n",
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"Please see the [Image Enhancers Documentation](docs/6.image_enhancers.md) to learn more.\n",
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"\n",
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"-----\n",
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"\n",
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"### *Original Information From The Stable Diffusion Repo*\n",
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"\n",
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"# Stable Diffusion\n",
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"\n",
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"*Stable Diffusion was made possible thanks to a collaboration with [Stability AI](https://stability.ai/) and [Runway](https://runwayml.com/) and builds upon our previous work:*\n",
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"\n",
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"[**High-Resolution Image Synthesis with Latent Diffusion Models**](https://ommer-lab.com/research/latent-diffusion-models/)<br/>\n",
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"[Robin Rombach](https://github.com/rromb)\\*,\n",
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"[Andreas Blattmann](https://github.com/ablattmann)\\*,\n",
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"[Dominik Lorenz](https://github.com/qp-qp)\\,\n",
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"[Patrick Esser](https://github.com/pesser),\n",
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"[Björn Ommer](https://hci.iwr.uni-heidelberg.de/Staff/bommer)<br/>\n",
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"\n",
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"**CVPR '22 Oral**\n",
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"\n",
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"which is available on [GitHub](https://github.com/CompVis/latent-diffusion). PDF at [arXiv](https://arxiv.org/abs/2112.10752). Please also visit our [Project page](https://ommer-lab.com/research/latent-diffusion-models/).\n",
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"\n",
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"[Stable Diffusion](#stable-diffusion-v1) is a latent text-to-image diffusion\n",
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"model.\n",
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"Thanks to a generous compute donation from [Stability AI](https://stability.ai/) and support from [LAION](https://laion.ai/), we were able to train a Latent Diffusion Model on 512x512 images from a subset of the [LAION-5B](https://laion.ai/blog/laion-5b/) database. \n",
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"Similar to Google's [Imagen](https://arxiv.org/abs/2205.11487), \n",
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"this model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text prompts.\n",
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"With its 860M UNet and 123M text encoder, the model is relatively lightweight and runs on a GPU with at least 10GB VRAM.\n",
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"See [this section](#stable-diffusion-v1) below and the [model card](https://huggingface.co/CompVis/stable-diffusion).\n",
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"\n",
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"## Stable Diffusion v1\n",
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"\n",
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"Stable Diffusion v1 refers to a specific configuration of the model\n",
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"architecture that uses a downsampling-factor 8 autoencoder with an 860M UNet\n",
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"and CLIP ViT-L/14 text encoder for the diffusion model. The model was pretrained on 256x256 images and \n",
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"then finetuned on 512x512 images.\n",
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"\n",
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"*Note: Stable Diffusion v1 is a general text-to-image diffusion model and therefore mirrors biases and (mis-)conceptions that are present\n",
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"in its training data. \n",
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"Details on the training procedure and data, as well as the intended use of the model can be found in the corresponding [model card](https://huggingface.co/CompVis/stable-diffusion).\n",
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"\n",
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"## Comments\n",
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"\n",
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"- Our codebase for the diffusion models builds heavily on [OpenAI's ADM codebase](https://github.com/openai/guided-diffusion)\n",
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" and [https://github.com/lucidrains/denoising-diffusion-pytorch](https://github.com/lucidrains/denoising-diffusion-pytorch). \n",
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" Thanks for open-sourcing!\n",
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"\n",
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"- The implementation of the transformer encoder is from [x-transformers](https://github.com/lucidrains/x-transformers) by [lucidrains](https://github.com/lucidrains?tab=repositories). \n",
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"\n",
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"## BibTeX\n",
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"\n",
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"```\n",
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"@misc{rombach2021highresolution,\n",
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" title={High-Resolution Image Synthesis with Latent Diffusion Models}, \n",
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" author={Robin Rombach and Andreas Blattmann and Dominik Lorenz and Patrick Esser and Björn Ommer},\n",
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" year={2021},\n",
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" eprint={2112.10752},\n",
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" archivePrefix={arXiv},\n",
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" primaryClass={cs.CV}\n",
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"}\n",
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"\n",
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"```"
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],
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"metadata": {
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"id": "z4kQYMPQn4d-"
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}
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Setup"
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],
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"metadata": {
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"id": "IZjJSr-WPNxB"
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}
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "eq0-E5mjSpmP"
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},
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"source": [
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"!nvidia-smi -L"
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],
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"!pip install condacolab\n",
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"import condacolab\n",
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"condacolab.install_from_url(\"https://github.com/conda-forge/miniforge/releases/download/4.14.0-0/Mambaforge-4.14.0-0-Linux-x86_64.sh\")\n",
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"\n",
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"import condacolab\n",
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"condacolab.check()\n",
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"\n",
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"# The runtime will crash after this, its normal as we are forcing a restart of the runtime from code. Just hit \"Run All\" again."
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],
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"metadata": {
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"id": "cDu33xkdJ5mD"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"!git clone https://github.com/Sygil-Dev/sygil-webui.git\n",
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"%cd /content/sygil-webui/\n",
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"!git checkout dev\n",
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"!git pull\n",
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"!wget -O arial.ttf https://github.com/matomo-org/travis-scripts/blob/master/fonts/Arial.ttf?raw=true"
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],
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"metadata": {
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"id": "pZHGf03Vp305"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"!mamba install cudatoolkit=11.3 git numpy=1.22.3 pip=20.3 python=3.8.5 pytorch=1.11.0 scikit-image=0.19.2 torchvision=0.12.0 -y"
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],
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"metadata": {
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"id": "dmN2igp5Yk3z"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"#@title Install dependencies.\n",
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"!python --version\n",
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"!pip install -r requirements.txt"
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],
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"metadata": {
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"id": "vXX0OaR8KyLQ"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
|
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"!npm install localtunnel"
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],
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"metadata": {
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"id": "FHyVuT5aSM2G"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"source": [
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"#Launch the WebUI"
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],
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"metadata": {
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"id": "csi6cj6gQZmC"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"#@title Mount Google Drive\n",
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"import os\n",
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"mount_google_drive = True #@param {type:\"boolean\"}\n",
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"save_outputs_to_drive = True #@param {type:\"boolean\"}\n",
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"\n",
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"if mount_google_drive:\n",
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" # Mount google drive to store your outputs.\n",
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" from google.colab import drive\n",
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" drive.mount('/content/drive/', force_remount=True)\n",
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"\n",
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"if save_outputs_to_drive:\n",
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" os.makedirs(\"/content/drive/MyDrive/sygil-webui/outputs\", exist_ok=True)\n",
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" os.symlink(\"/content/drive/MyDrive/sygil-webui/outputs\", \"/content/sygil-webui/outputs\", target_is_directory=True)\n"
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],
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"metadata": {
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"id": "pcSWo9Zkzbsf"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"#@title Enter Huggingface token\n",
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"!git config --global credential.helper store\n",
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"!huggingface-cli login"
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],
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"metadata": {
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"id": "IsbG7fvIrKwg"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"source": [
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"#@title <-- Press play on the music player to keep the tab alive (Uses only 13MB of data)\n",
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"%%html\n",
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"<b>Press play on the music player to keep the tab alive, then start your generation below (Uses only 13MB of data)</b><br/>\n",
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"<audio src=\"https://henk.tech/colabkobold/silence.m4a\" controls>"
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],
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"metadata": {
|
|
"id": "-WknaU7uu_q6"
|
|
},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
|
|
"source": [
|
|
"JS to prevent idle timeout:\n",
|
|
"\n",
|
|
"Press F12 OR CTRL + SHIFT + I OR right click on this website -> inspect. Then click on the console tab and paste in the following code.\n",
|
|
"\n",
|
|
"function ClickConnect(){\n",
|
|
"console.log(\"Working\");\n",
|
|
"document.querySelector(\"colab-toolbar-button#connect\").click()\n",
|
|
"}\n",
|
|
"setInterval(ClickConnect,60000)"
|
|
],
|
|
"metadata": {
|
|
"id": "pjIjiCuJysJI"
|
|
}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"source": [
|
|
"#@title Open port 8501 and start Streamlit server. Open link in 'link.txt' file in file pane on left.\n",
|
|
"!npx localtunnel --port 8501 &>/content/link.txt &\n",
|
|
"!streamlit run scripts/webui_streamlit.py --theme.base dark --server.headless true true 2>&1 | tee -a /content/log.txt"
|
|
],
|
|
"metadata": {
|
|
"id": "5whXm2nfSZ39"
|
|
},
|
|
"execution_count": null,
|
|
"outputs": []
|
|
}
|
|
]
|
|
}
|