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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 | |