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# Loaders

There are many ways to train adapter neural networks for diffusion models, such as 
- [Textual Inversion](./training/text_inversion.mdx)
- [LoRA](https://github.com/cloneofsimo/lora)
- [Hypernetworks](https://arxiv.org/abs/1609.09106)

Such adapter neural networks often only consist of a fraction of the number of weights compared 
to the pretrained model and as such are very portable. The Diffusers library offers an easy-to-use
API to load such adapter neural networks via the [`loaders.py` module](https://github.com/huggingface/diffusers/blob/main/src/diffusers/loaders.py). 

**Note**: This module is still highly experimental and prone to future changes.

## LoaderMixins

### UNet2DConditionLoadersMixin

[[autodoc]] loaders.UNet2DConditionLoadersMixin

### TextualInversionLoaderMixin

[[autodoc]] loaders.TextualInversionLoaderMixin

### LoraLoaderMixin

[[autodoc]] loaders.LoraLoaderMixin

### FromCkptMixin

[[autodoc]] loaders.FromCkptMixin
