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