This version is a bit more optimized, and better packaged. Also the model has been trained longer, so when the weights become publicly available the resulting quality should be much higher.

There's also Disco Diffusion: https://www.reddit.com/r/DiscoDiffusion/

Not sure how they compare. DD seems to be quite popular. I'm currently setting up DD locally.

I've been running DD for a few months now... I tend to just edit the python script or use e.g. entmike's fork which can read config files to make changes to the 50+ parameters (basically everything is better than having to use Jupyter Notebooks IMO), granted if you don't have a GPU with 6+ GB of VRAM, you can often get a decent enough GPU for free from Google Colab. For running locally, I can also highly recommend Visions of Chaos, which includes multiple versions/forks of Disco Diffusion, as well as a ton of other latent diffusion scripts, not to mention many many many other generation features such as fractals and even music. They also recently added the ability to train your own diffusion models which I've been doing the last few days using thousands of my own photographs. It also has a pretty nice GUI and the dev is extremely responsive on Discord. Also after you do the setup for VoC it handles running all the python venv setup stuff otherwise necessary with local DD installs. In any case, check out DD Discord and/or VoC discord for lots of info, tips, help, examples, and support.

Thanks for the info. It is possible to do something like transfer learning on top of existing models or do you train your own models from scratch? I'll check out that Vision of Chaos thing. I'm just beginning my journey into this generative art stuff and just basically trying to get this running right now.

Well there are 2 types of models, CLIP and diffusion models. With VoC, Disco, etc. latent diffusion, you pick multiple CLIP models and a single diffusion model. The CLIP models are the big gigabyte ones like ViT and RN, and you can use CLIP search engines that search on the LAION datasets to give you a rough idea what will happen when you use those words in your prompts: https://rom1504.github.io/clip-retrieval

I will otherwise refer you to the "Bible" of latent diffusion: https://sweet-hall-e72.notion.site/A-Traveler-s-Guide-to-the...

Whatever isn't covered in there is probably in the Disco Diffusion cheatsheet: https://botbox.dev/disco-diffusion-cheatsheet/

There are tons of resources out there, and it's a nonstop learning and experimenting process to try to achieve what you want.

Thanks again. Now I got my first image out and it ended up being a complete failure. :) I'll keep experimenting / learning.

Welcome to the party! My first image was also a total failure, it can only get better from here ;) Prepare to spend a lot of time reading before you start to make sense of things.