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This is a fork of CompVis/stable-diffusion, the open source text-to-image generator. It provides a streamlined process with various new features and options to aid the image generation process. It runs on Windows, Mac and Linux machines, and runs on GPU cards with as little as 4 GB or RAM.
Note: This fork is rapidly evolving. Please use the Issues tab to report bugs and make feature requests. Be sure to use the provided templates. They will help aid diagnose issues faster.
This repository was formally known as lstein/stable-diffusion
This fork is supported across multiple platforms. You can find individual installation instructions below.
You wil need one of the following:
If you are have a Nvidia 10xx series card (e.g. the 1080ti), please run the dream script in full-precision mode as shown below.
Similarly, specify full-precision mode on Apple M1 hardware.
To run in full-precision mode, start
dream.py with the
(ldm) ~/stable-diffusion$ python scripts/dream.py --full_precision
v1.14 (11 September 2022)
v1.13 (3 September 2022
For older changelogs, please visit CHANGELOGS.
Please check out our Q&A to get solutions for common installation problems and other issues.
Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code cleanup, testing, or code reviews, is very much encouraged to do so. If you are unfamiliar with how to contribute to GitHub projects, here is a Getting Started Guide.
A full set of contribution guidelines, along with templates, are in progress, but for now the most important thing is to make your pull request against the "development" branch, and not against "main". This will help keep public breakage to a minimum and will allow you to propose more radical changes.
This fork is a combined effort of various people from across the world. Check out the list of all these amazing people. We thank them for their time, hard work and effort.
For support, please use this repository's GitHub Issues tracking service. Feel free to send me an email if you use and like the script.
Original portions of the software are Copyright (c) 2020 Lincoln D. Stein (https://github.com/lstein)
Please see the original README for more information on this software and underlying algorithm, located in the file README-CompViz.md.