sd-multi - run multiple Stable Diffusion systems in Docker

Purpose

I've noticed that some forks of Stable Diffusion, while very active, often break. This repo adds a little bit of stability and predictability, while at the same time allowing the freedom to (relatively easily) play around with different forks/frontends/systems and their features.

Docker is used to provide some isolation between various systems' dependencies beyond what Anaconda can do. It also consolidates input and output locations.

Usage

For a detailed description of how to get this working in Windows using WSL2 and native Docker (not Docker Desktop), see this blog post.

Prerequisites

A modern Nvidia GPU
Windows 10/11 with WSL2 or native Linux
Lots of free disk space (200+ GB recommended if experimenting)
Docker CE installed
Docker Compose plugin installed
Nvidia Container Toolkit installed
Git installed in WSL2/Linux
The file sd-v1-4.ckpt and/or v1-5-pruned-emaonly.ckpt from Hugging Face (free registration required)
- Alternatively, after registering for a Hugging Face account, you can generate a new token for automatic downloading

Steps

Clone this repo to, say, your home directory, and then cd into it:

cd ~
git clone https://github.com/arktronic/sd-multi.git
cd sd-multi

If not using a Hugging Face token, place the sd-v1-4.ckpt and/or v1-5-pruned-emaonly.ckpt file you downloaded earlier into ~/sd-multi/res/
If you do have a Hugging Face token, copy env.example to .env inside ~/sd-multi and edit the .env file:
- Uncomment the #HUGGINGFACE_TOKEN= line by removing the # in front
- Insert your Hugging Face token after the equals sign, like so: HUGGINGFACE_TOKEN=hf_asdfasdfasdfasdfasdf
Run ./verify-resources.sh -d to verify and download any missing models or weights
- If you encounter any issues, please make sure they are resolved before continuing to the next step
Launch one of the supported forks! (see the fork options below)