a1111-sd-webui-locon VS LyCORIS

Workaround in the bottom of this thread: https://github.com/KohakuBlueleaf/a1111-sd-webui-locon/issues/40

And are you sure they're not Loha or LoCON instead of LoRA? Try Additional Networks, but you may need this extension instead/as well. I ended up having to delete Additional Networks because it was causing problems. I don't know if it's fixed.

Click the green button on the github page for the extension and in the pop-up click on the little icon that looks like two squares overlapping to copy the link.

I installed the webui locon from here:https://github.com/KohakuBlueleaf/a1111-sd-webui-locon/blob/main/scripts/main.py

Auto1111 has integrated the Locon version of LoRA to its built in extensions. Meaning that the KohakuBlueleaf extension is in conflict with the built in LoRA extension and must be removed. I tested this and my render came out just as expected with a LoRA applied.

They seem to use this extension , but I can't figure out what is even different about it. Does anyone know?

Also earlier I received failed to match lora keys error or something like that and I had to install this extension to make it go away. The output is different when there's an error like this. https://github.com/KohakuBlueleaf/a1111-sd-webui-locon

Lycoris is another implementation of LoRA done by KohakuBlueleaf: https://github.com/KohakuBlueleaf/LyCORIS

Most guides focus on LoRa training as that has been around for longer. But I think LoHa can give better results. But the training is about half as fas it/s and it requires different training settings.

I've read in some tutorials that it is best that the value should be 64 or below, also here they suggest to not go over 64 ( https://github.com/KohakuBlueleaf/LyCORIS )

Does anyone know how to make LyCORIS models (https://github.com/KohakuBlueleaf/LyCORIS) work with inpainting models?

I think it was linked already but this is also relevant for LoRa: https://github.com/KohakuBlueleaf/LyCORIS Nice work!

There are some WIP evolutions of SD Lora in the works, like locon and lycoris.

https://github.com/KohakuBlueleaf/LyCORIS

You might want to expand LoRA to include LoCon and LoHa, (and also add a column for VRAM requirements) (Think of it as a more complete LoRA that works for the kernels in the convolutional units rather than just the weights for the feed-forward network), support is still quite limited, but it's starting to pick up steam https://github.com/KohakuBlueleaf/LyCORIS