huggingface--transformers/docs/source/en/pipeline_gradio.md

Machine learning apps

Gradio, a fast and easy library for building and sharing machine learning apps, is integrated with [Pipeline] to quickly create a simple interface for inference.

Before you begin, make sure Gradio is installed.

!pip install gradio

Create a pipeline for your task, and then pass it to Gradio's Interface.from_pipeline function to create the interface. Gradio automatically determines the appropriate input and output components for a [Pipeline].

Add launch to create a web server and start up the app.

from transformers import pipeline
import gradio as gr

pipeline = pipeline("image-classification", model="google/vit-base-patch16-224")
gr.Interface.from_pipeline(pipeline).launch()

The web app runs on a local server by default. To share the app with other users, set share=True in launch to generate a temporary public link. For a more permanent solution, host the app on Hugging Face Spaces.

gr.Interface.from_pipeline(pipeline).launch(share=True)

The Space below is created with the code above and hosted on Spaces.