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| 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) |
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| 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). |
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| **Note**: This module is still highly experimental and prone to future changes. |
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| [[autodoc]] loaders.UNet2DConditionLoadersMixin |
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