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updated doc for stable diffusion pipelines #1770

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13 changes: 9 additions & 4 deletions docs/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -126,21 +126,26 @@ When adding a new pipeline:
- Paper abstract
- Tips and tricks and how to use it best
- Possible an end-to-end example of how to use it
- Add all the pipeline classes that should be linked in the diffusion model. These classes should be added using our Markdown syntax. Usually as follows:
- Add all the pipeline classes that should be linked in the diffusion model. These classes should be added using our Markdown syntax. By default as follows:

```
## XXXPipeline

[[autodoc]] XXXPipeline
- all
- __call__
```

This will include every public method of the pipeline that is documented. You can specify which methods should be in the docs:
This will include every public method of the pipeline that is documented, as well as the `__call__` method that is not documented by default. If you just want to add additional methods that are not documented, you can put the list of all methods to add in a list that contains `all`.

```
## XXXPipeline

[[autodoc]] XXXPipeline
- all
- __call__
- enable_attention_slicing
- disable_attention_slicing
- enable_xformers_memory_efficient_attention
- disable_xformers_memory_efficient_attention
```

You can follow the same process to create a new scheduler under the `docs/source/api/schedulers` folder
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17 changes: 16 additions & 1 deletion docs/source/_toctree.yml
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Expand Up @@ -91,6 +91,7 @@
- local: api/outputs
title: "Outputs"
title: "Main Classes"

- sections:
- local: api/pipelines/overview
title: "Overview"
Expand All @@ -112,7 +113,21 @@
title: "PNDM"
- local: api/pipelines/score_sde_ve
title: "Score SDE VE"
- local: api/pipelines/stable_diffusion
- sections:
- local: api/pipelines/stable_diffusion/overview
title: "Overview"
- local: api/pipelines/stable_diffusion/text2img
title: "Text-to-Image"
- local: api/pipelines/stable_diffusion/img2img
title: "Image-to-Image"
- local: api/pipelines/stable_diffusion/inpaint
title: "Inpaint"
- local: api/pipelines/stable_diffusion/depth2img
title: "Depth-to-Image"
- local: api/pipelines/stable_diffusion/image_variation
title: "Image-Variation"
- local: api/pipelines/stable_diffusion/upscale
title: "Super-Resolution"
title: "Stable Diffusion"
- local: api/pipelines/stable_diffusion_2
title: "Stable Diffusion 2"
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2 changes: 1 addition & 1 deletion docs/source/api/pipelines/alt_diffusion.mdx
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Expand Up @@ -28,7 +28,7 @@ The abstract of the paper is the following:

## Tips

- AltDiffusion is conceptually exaclty the same as [Stable Diffusion](./api/pipelines/stable_diffusion).
- AltDiffusion is conceptually exaclty the same as [Stable Diffusion](./api/pipelines/stable_diffusion/overview).

- *Run AltDiffusion*

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33 changes: 33 additions & 0 deletions docs/source/api/pipelines/stable_diffusion/depth2img.mdx
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@@ -0,0 +1,33 @@
<!--Copyright 2022 The HuggingFace Team. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->

# Depth-to-Image Generation
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## StableDiffusionDepth2ImgPipeline

The depth-guided stable diffusion model was created by the researchers and engineers from [CompVis](https://github.com/CompVis), [Stability AI](https://stability.ai/), and [LAION](https://laion.ai/), as part of Stable Diffusion 2.0. It uses [MiDas](https://github.com/isl-org/MiDaS) to infer depth based on an image.

[`StableDiffusionDepth2ImgPipeline`] lets you pass a text prompt and an initial image to condition the generation of new images as well as a `depth_map` to preserve the images’ structure.

The original codebase can be found here:
- *Stable Diffusion v2*: [Stability-AI/stablediffusion](https://github.com/Stability-AI/stablediffusion#depth-conditional-stable-diffusion)

Available Checkpoints are:
- *stable-diffusion-2-depth*: [stabilityai/stable-diffusion-2-depth](https://huggingface.co/stabilityai/stable-diffusion-2-depth)

[[autodoc]] StableDiffusionDepth2ImgPipeline
- all
- __call__
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- enable_attention_slicing
- disable_attention_slicing
- enable_xformers_memory_efficient_attention
- disable_xformers_memory_efficient_attention
31 changes: 31 additions & 0 deletions docs/source/api/pipelines/stable_diffusion/image_variation.mdx
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@@ -0,0 +1,31 @@
<!--Copyright 2022 The HuggingFace Team. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->

# Image Variation
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## StableDiffusionImageVariationPipeline

[`StableDiffusionImageVariationPipeline`] lets you generate variations from an input image using Stable Diffusion. It uses a fine-tuned version of Stable Diffusion model, trained by [Justin Pinkney](https://www.justinpinkney.com/) (@Buntworthy) at [Lambda](https://lambdalabs.com/)

The original codebase can be found here:
[Stable Diffusion Image Variations](https://github.com/LambdaLabsML/lambda-diffusers#stable-diffusion-image-variations)

Available Checkpoints are:
- *sd-image-variations-diffusers*: [lambdalabs/sd-image-variations-diffusers](https://huggingface.co/lambdalabs/sd-image-variations-diffusers)

[[autodoc]] StableDiffusionImageVariationPipeline
- all
- __call__
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- enable_attention_slicing
- disable_attention_slicing
- enable_xformers_memory_efficient_attention
- disable_xformers_memory_efficient_attention
29 changes: 29 additions & 0 deletions docs/source/api/pipelines/stable_diffusion/img2img.mdx
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@@ -0,0 +1,29 @@
<!--Copyright 2022 The HuggingFace Team. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->

# Image-to-Image Generation

## StableDiffusionImg2ImgPipeline

The Stable Diffusion model was created by the researchers and engineers from [CompVis](https://github.com/CompVis), [Stability AI](https://stability.ai/), [runway](https://github.com/runwayml), and [LAION](https://laion.ai/). The [`StableDiffusionImg2ImgPipeline`] lets you pass a text prompt and an initial image to condition the generation of new images using Stable Diffusion.

The original codebase can be found here: [CampVis/stable-diffusion](https://github.com/CompVis/stable-diffusion/blob/main/scripts/img2img.py)

[`StableDiffusionImg2ImgPipeline`] is compatible with all Stable Diffusion checkpoints for [Text-to-Image](./text2img)

[[autodoc]] StableDiffusionImg2ImgPipeline
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- all
- __call__
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- enable_attention_slicing
- disable_attention_slicing
- enable_xformers_memory_efficient_attention
- disable_xformers_memory_efficient_attention
33 changes: 33 additions & 0 deletions docs/source/api/pipelines/stable_diffusion/inpaint.mdx
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<!--Copyright 2022 The HuggingFace Team. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->

# Text-Guided Image Inpainting

## StableDiffusionInpaintPipeline

The Stable Diffusion model was created by the researchers and engineers from [CompVis](https://github.com/CompVis), [Stability AI](https://stability.ai/), [runway](https://github.com/runwayml), and [LAION](https://laion.ai/). The [`StableDiffusionInpaintPipeline`] lets you edit specific parts of an image by providing a mask and a text prompt using Stable Diffusion.

The original codebase can be found here:
- *Stable Diffusion V1*: [CampVis/stable-diffusion](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion)
- *Stable Diffusion V2*: [Stability-AI/stablediffusion](https://github.com/Stability-AI/stablediffusion#image-inpainting-with-stable-diffusion)

Available checkpoints are:
- *stable-diffusion-inpainting (512x512 resolution)*: [runwayml/stable-diffusion-inpainting](https://huggingface.co/runwayml/stable-diffusion-inpainting)
- *stable-diffusion-2-inpainting (512x512 resolution)*: [stabilityai/stable-diffusion-2-inpainting](https://huggingface.co/stabilityai/stable-diffusion-2-inpainting)

[[autodoc]] StableDiffusionInpaintPipeline
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- all
- __call__
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- enable_attention_slicing
- disable_attention_slicing
- enable_xformers_memory_efficient_attention
- disable_xformers_memory_efficient_attention
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Expand Up @@ -25,9 +25,14 @@ For more details about how Stable Diffusion works and how it differs from the ba

| Pipeline | Tasks | Colab | Demo
|---|---|:---:|:---:|
| [pipeline_stable_diffusion.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py) | *Text-to-Image Generation* | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_diffusion.ipynb) | [🤗 Stable Diffusion](https://huggingface.co/spaces/stabilityai/stable-diffusion)
| [pipeline_stable_diffusion_img2img.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py) | *Image-to-Image Text-Guided Generation* | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/image_2_image_using_diffusers.ipynb) | [🤗 Diffuse the Rest](https://huggingface.co/spaces/huggingface/diffuse-the-rest)
| [pipeline_stable_diffusion_inpaint.py](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py) | **Experimental** – *Text-Guided Image Inpainting* | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/in_painting_with_stable_diffusion_using_diffusers.ipynb) | Coming soon
| [StableDiffusionPipeline](./text2img) | *Text-to-Image Generation* | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_diffusion.ipynb) | [🤗 Stable Diffusion](https://huggingface.co/spaces/stabilityai/stable-diffusion)
| [StableDiffusionImg2ImgPipeline](./img2img) | *Image-to-Image Text-Guided Generation* | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/image_2_image_using_diffusers.ipynb) | [🤗 Diffuse the Rest](https://huggingface.co/spaces/huggingface/diffuse-the-rest)
| [StableDiffusionInpaintPipeline](./inpaint) | **Experimental** – *Text-Guided Image Inpainting* | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/in_painting_with_stable_diffusion_using_diffusers.ipynb) | Coming soon
| [StableDiffusionDepth2ImgPipeline](./depth2img) | **Experimental** – *Depth-to-Image Text-Guided Generation * | | Coming soon
| [StableDiffusionImageVariationPipeline](./image_variation) | **Experimental** – *Image Variation Generation * | | [🤗 Stable Diffusion Image Variations](https://huggingface.co/spaces/lambdalabs/stable-diffusion-image-variations)
| [StableDiffusionUpscalePipeline](./upscale) | **Experimental** – *Text-Guided Image Super-Resolution * | | Coming soon



## Tips

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39 changes: 39 additions & 0 deletions docs/source/api/pipelines/stable_diffusion/text2img.mdx
Original file line number Diff line number Diff line change
@@ -0,0 +1,39 @@
<!--Copyright 2022 The HuggingFace Team. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->

# Text-to-Image Generation
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## StableDiffusionPipeline

The Stable Diffusion model was created by the researchers and engineers from [CompVis](https://github.com/CompVis), [Stability AI](https://stability.ai/), [runway](https://github.com/runwayml), and [LAION](https://laion.ai/). The [`StableDiffusionPipeline`] is capable of generating photo-realistic images given any text input using Stable Diffusion.

The original codebase can be found here:
- *Stable Diffusion V1*: [CampVis/stable-diffusion](https://github.com/CompVis/stable-diffusion)
- *Stable Diffusion v2*: [Stability-AI/stablediffusion](https://github.com/Stability-AI/stablediffusion)

Available Checkpoints are:
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- *stable-diffusion-v1-4 (512x512 resolution)* [CompVis/stable-diffusion-v1-4](https://huggingface.co/CompVis/stable-diffusion-v1-4)
- *stable-diffusion-v1-5 (512x512 resolution)* [runwayml/stable-diffusion-v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5)
- *stable-diffusion-2-base (512x512 resolution)*: [stabilityai/stable-diffusion-2-base](https://huggingface.co/stabilityai/stable-diffusion-2-base)
- *stable-diffusion-2 (768x768 resolution)*: [stabilityai/stable-diffusion-2](https://huggingface.co/stabilityai/stable-diffusion-2)
- *stable-diffusion-2-1-base (512x512 resolution)* [stabilityai/stable-diffusion-2-1-base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base)
- *stable-diffusion-2-1 (768x768 resolution)*: [stabilityai/stable-diffusion-2-1](https://huggingface.co/stabilityai/stable-diffusion-2-1)

[[autodoc]] StableDiffusionPipeline
- all
- __call__
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- enable_attention_slicing
- disable_attention_slicing
- enable_vae_slicing
- disable_vae_slicing
- enable_xformers_memory_efficient_attention
- disable_xformers_memory_efficient_attention
32 changes: 32 additions & 0 deletions docs/source/api/pipelines/stable_diffusion/upscale.mdx
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@@ -0,0 +1,32 @@
<!--Copyright 2022 The HuggingFace Team. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->

# Super-Resolution

## StableDiffusionUpscalePipeline

The upscaler diffusion model was created by the researchers and engineers from [CompVis](https://github.com/CompVis), [Stability AI](https://stability.ai/), and [LAION](https://laion.ai/), as part of Stable Diffusion 2.0. [`StableDiffusionUpscalePipeline`] can be used to enhance the resolution of input images by a factor of 4.

The original codebase can be found here:
- *Stable Diffusion v2*: [Stability-AI/stablediffusion](https://github.com/Stability-AI/stablediffusion#image-upscaling-with-stable-diffusion)

Available Checkpoints are:
- *stabilityai/stable-diffusion-x4-upscaler (x4 resolution resolution)*: [stable-diffusion-x4-upscaler](https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler)


[[autodoc]] StableDiffusionUpscalePipeline
- all
- __call__
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- enable_attention_slicing
- disable_attention_slicing
- enable_xformers_memory_efficient_attention
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