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15 changes: 6 additions & 9 deletions docs/source/api/models.mdx
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Expand Up @@ -22,12 +22,15 @@ The models are built on the base class ['ModelMixin'] that is a `torch.nn.module
## UNet2DOutput
[[autodoc]] models.unet_2d.UNet2DOutput

## UNet1DModel
[[autodoc]] UNet1DModel

## UNet2DModel
[[autodoc]] UNet2DModel

## UNet1DOutput
[[autodoc]] models.unet_1d.UNet1DOutput

## UNet1DModel
[[autodoc]] UNet1DModel

## UNet2DConditionOutput
[[autodoc]] models.unet_2d_condition.UNet2DConditionOutput

Expand All @@ -37,12 +40,6 @@ The models are built on the base class ['ModelMixin'] that is a `torch.nn.module
## DecoderOutput
[[autodoc]] models.vae.DecoderOutput

## UNet1DModel
[[autodoc]] UNet1DModel

## UNet1DOutput
[[autodoc]] models.unet_1d.UNet1DOutput

## VQEncoderOutput
[[autodoc]] models.vae.VQEncoderOutput

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5 changes: 3 additions & 2 deletions examples/README.md
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Expand Up @@ -36,9 +36,10 @@ If you feel like another important example should exist, we are more than happy

Training examples show how to pretrain or fine-tune diffusion models for a variety of tasks. Currently we support:

| Task | 🤗 Accelerate | 🤗 Datasets | Colab
|---|---|:---:|:---:|
| Task | 🤗 Accelerate | 🤗 Datasets | Colab
|---------------------------------------------------------------------------------------------------------------------------------------------------------|---|:---:|:---:|
| [**Unconditional Image Generation**](https://github.com/huggingface/diffusers/blob/main/examples/unconditional_image_generation/train_unconditional.py) | ✅ | ✅ | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/training_example.ipynb)
| [**Reinforcement Learning for Control**](https://github.com/huggingface/diffusers/blob/main/examples/rl/run_diffusers_locomotion.py) | | | coming soon.

## Community

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69 changes: 0 additions & 69 deletions examples/diffuser/run_diffuser_value_guided.py

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