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

* gradio docs

* Update docs/source/en/api/pipelines/stable_diffusion/overview.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* changes

* changes

* changes

* 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>

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

@@ -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. 
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