min-dalle VS disco-diffusion

min(DALL·E).

Additionally, it's also open-sourced on GitHub and can be self-hosted, with easy instructions to do so: https://github.com/kuprel/min-dalle

For CPU, even highly-optimized models like mindalle are prohibitively slow.

Maybe you would be interested in this GitHub repo.

These were generated with DALL-E Mega via min-dalle, which is a more advanced version of DALL-E Mini with better visual fidelity (less blurry) but otherwise similar results.

GitHub repo (contains links to Colab notebook and web app at site Replicate[dot]com). The times mentioned in the title don't included setup time.

Disco-diffusion, a framework like Stable, which came out about 13 months ago: https://github.com/alembics/disco-diffusion

Runner-ups are Craiyon (for being more "creative" than SD), Disco Diffusion, minDALL-E, and CLIP Guided Diffusion.

From the Disco Diffusion GitHub, "“A frankensteinian amalgamation of notebooks, models and techniques for the generation of AI Art and Animations.”

Google Colab is probably the easiest way to run DD. To find the most recent version go to the GitHub page and then open the link to the Colab. Initially, you'll probably just want to experiment with the prompts. But there's also Zippy's Disco Diffusion Cheatsheet v0.3 which can be a useful place to learn more.

You can probably port Disco Diffusion pretty easily. It’s available on Google Colab, so should be straightforward. Their GitHub is: https://github.com/alembics/disco-diffusion

https://www.reddit.com/r/DiscoDiffusion/, https://github.com/alembics/disco-diffusion. As far as I'm aware the only way to use this is via Google Colab. Rather difficult to use because of this.

https://github.com/alembics/disco-diffusion,