diffusion-ui VS diffusers

You can use diffusion-ui on top of automatic1111 for easy outpainting. Run automatic1111 with --cors-allow-origins=http://127.0.0.1:5173,https://diffusionui.com Then select the automatic1111 backend, upload an image then use the mouse scroll to zoom out.

I see you've got my https://github.com/leszekhanusz/diffusion-ui gui but it seems to be linked to a completely unrelated face-swapping interface?

Yes, checkout diffusion-ui

I modified my GUI Stable Diffusion frontend to be able to use the automatic1111 fork as a backend.

It's not really well known at the moment but you also have my DiffusionUI interface which is based on diffusers with a backend where you can disable the nsfw filter.

GitHub: https://github.com/leszekhanusz/diffusion-ui

One way to do it is to use diffusionui, a web interface I made in vue. Here is a crappy video demo showing the process.

If you want to do inpainting, you can try my diffusionui interface I'll add a feature soon to save the generated images in local storage in the browser. Here is a small demo

It's still a work in progress but you can already play with it. Check it on GitHub

I'm missing something about the random factor, from the sample code from https://github.com/huggingface/diffusers/blob/main/README.md

Hey people, I noticed that combining these two methods in a single forward pass increases the controllability of the generation quite a bit. I was kind of puzzled that sometimes ControlNet yielded better results than T2IAdapter for some cases, and sometimes it was the other way around, so I decided to test both at the same time, and results were quite nice. Some visuals and more motivation here: https://github.com/huggingface/diffusers/issues/5847 And it was already merged here: https://github.com/huggingface/diffusers/pull/5869

Open Parti Prompts: The better way to evaluate diffusion models (repo)

You have disabled the safety checker for by passing `safety_checker=None`. Ensure that you abide to the conditions of the Stable Diffusion license and do not expose unfiltered results in services or applications open to the public. Both the diffusers team and Hugging Face strongly recommend to keep the safety filter enabled in all public facing circumstances, disabling it only for use-cases that involve analyzing network behavior or auditing its results. For more information, please have a look at https://github.com/huggingface/diffusers/pull/254 .

For developers, TensorRT support also exists for the diffusers library via community pipelines. [1] It's limited, but if you're only supporting a subset of features, it can help.

In general, these insane speed boosts comes at the cost of bleeding edge features.

[1] https://github.com/huggingface/diffusers/blob/28e8d1f6ec82a6...

I was training sdxl UNET base model, with the diffusers library, which was going great until around step 210k when the weights suddenly turned back to their original values and stayed that way. I also tried with the ema version, which didn't change at all. I also looked at the tensor's weight values directly which confirmed my suspicions.

Merging LoRAs is essentially taking a weighted average of the LoRA adapter weights. It's more common in other UIs.

diffusers is working on a PR for it: https://github.com/huggingface/diffusers/pull/4473