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Adds docs for gradio.Interface.from_pipeline() (#7346)

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* gradio docs

* Update docs/source/en/api/pipelines/stable_diffusion/overview.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

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* Update docs/source/en/api/pipelines/stable_diffusion/overview.md

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
This commit is contained in:
Abubakar Abid
2024-03-15 18:41:28 -07:00
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docs/source/en/api/pipelines/stable_diffusion/overview.md
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@@ -172,3 +172,41 @@ inpaint = StableDiffusionInpaintPipeline(**text2img.components)
# now you can use text2img(...), img2img(...), inpaint(...) just like the call methods of each respective pipeline
```
### Create web demos using `gradio`
The Stable Diffusion pipelines are automatically supported in [Gradio](https://github.com/gradio-app/gradio/), a library that makes creating beautiful and user-friendly machine learning apps on the web a breeze. First, make sure you have Gradio installed:
```
pip install -U gradio
```
Then, create a web demo around any Stable Diffusion-based pipeline. For example, you can create an image generation pipeline in a single line of code with Gradio's [`Interface.from_pipeline`](https://www.gradio.app/docs/interface#interface-from-pipeline) function:
```py
from diffusers import StableDiffusionPipeline
import gradio as gr
pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4")
gr.Interface.from_pipeline(pipe).launch()
```
which opens an intuitive drag-and-drop interface in your browser:
![](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/gradio-panda.png)
Similarly, you could create a demo for an image-to-image pipeline with:
```py
from diffusers import StableDiffusionImg2ImgPipeline
import gradio as gr
pipe = StableDiffusionImg2ImgPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
gr.Interface.from_pipeline(pipe).launch()
```
By default, the web demo runs on a local server. If you'd like to share it with others, you can generate a temporary public
link by setting `share=True` in `launch()`. Or, you can host your demo on [Hugging Face Spaces](https://huggingface.co/spaces)https://huggingface.co/spaces for a permanent link.