diffusers VS sd-webui-additional-networks

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

In the input field labeled "URL for extension's git repository," paste the following link: https://github.com/kohya-ss/sd-webui-additional-networks.git

Yes, this one: https://github.com/kohya-ss/sd-webui-additional-networks

Seems that calling Loras from the prompt is bugged right now. Install "Additional Networks" (https://github.com/kohya-ss/sd-webui-additional-networks) and use them from the GUI, without mentioning it in the prompt at all:

Use the additional networks extension Download your lora and place it into "stable-diffusion-webui\extensions\sd-webui-additional-networks\models\lora". Now you can select the lora in the additonal networks tab in your web ui and set a weight. Afterwards you can just generate your image.

sd-webui-additional-networks: wouldn't be necessary, but it has more functions than the basic web-ui integration.

📷 If you are getting the error "failed to match keys when loading Lora" it means you are either on the native Lora integration of Automatic1111 which may not support LoCon, please install the https://github.com/kohya-ss/sd-webui-additional-networks extension to solve the issue.

if you use civitai, you can use this extension, if you have this Lora extension, you can edit the meta data and load it from there.

I have both https://github.com/kohya-ss/sd-webui-additional-networks and https://github.com/KohakuBlueleaf/a1111-sd-webui-lycoris because i was told these are the ones i needed for LyCORIS to work. IT did for a while but since recently it has stopped working altogether.

This does not require the use of the Latent Couple(Two-Shot) extension. This requires the Additional Networks Extension, which may already be in your Stable Diffusion install or can be installed from https://github.com/kohya-ss/sd-webui-additional-networks through the extensions tab as shown below.