LoRA

LoRA is a fast and lightweight training method that inserts and trains a significantly smaller number of parameters instead of all the model parameters. This produces a smaller file (~100 MBs) and makes it easier to quickly train a model to learn a new concept. LoRA weights are typically loaded into the denoiser, text encoder or both. The denoiser usually corresponds to a UNet ([UNet2DConditionModel], for example) or a Transformer ([SD3Transformer2DModel], for example). There are several classes for loading LoRA weights:

[StableDiffusionLoraLoaderMixin] provides functions for loading and unloading, fusing and unfusing, enabling and disabling, and more functions for managing LoRA weights. This class can be used with any model.
[StableDiffusionXLLoraLoaderMixin] is a Stable Diffusion (SDXL) version of the [StableDiffusionLoraLoaderMixin] class for loading and saving LoRA weights. It can only be used with the SDXL model.
[SD3LoraLoaderMixin] provides similar functions for Stable Diffusion 3.
[FluxLoraLoaderMixin] provides similar functions for Flux.
[CogVideoXLoraLoaderMixin] provides similar functions for CogVideoX.
[Mochi1LoraLoaderMixin] provides similar functions for Mochi.
[AmusedLoraLoaderMixin] is for the [AmusedPipeline].
[LoraBaseMixin] provides a base class with several utility methods to fuse, unfuse, unload, LoRAs and more.

To learn more about how to load LoRA weights, see the LoRA loading guide.

StableDiffusionLoraLoaderMixin

[[autodoc]] loaders.lora_pipeline.StableDiffusionLoraLoaderMixin

StableDiffusionXLLoraLoaderMixin

[[autodoc]] loaders.lora_pipeline.StableDiffusionXLLoraLoaderMixin

SD3LoraLoaderMixin

[[autodoc]] loaders.lora_pipeline.SD3LoraLoaderMixin

FluxLoraLoaderMixin

[[autodoc]] loaders.lora_pipeline.FluxLoraLoaderMixin

CogVideoXLoraLoaderMixin

[[autodoc]] loaders.lora_pipeline.CogVideoXLoraLoaderMixin

Mochi1LoraLoaderMixin

[[autodoc]] loaders.lora_pipeline.Mochi1LoraLoaderMixin

AmusedLoraLoaderMixin

[[autodoc]] loaders.lora_pipeline.AmusedLoraLoaderMixin

LoraBaseMixin

[[autodoc]] loaders.lora_base.LoraBaseMixin