Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere!
import gradio as gr
def sketch_recognition(img):
# Implement sketch recognition model here...
# Return labels and confidences as dictionary
iface = gr.Interface(fn=sketch_recognition, inputs="image", outputs="label").launch()
Gradio can be installed directly through pip. Creating a Gradio interface only requires adding a couple lines of code to your project. You can choose from a variety of interface types to interface your function.
Read more on Getting Started...
Gradio can be embedded in Python notebooks or presented as a webpage. A Gradio interface can automatically generate a public link you can share with colleagues that lets them interact with the model on your computer remotely from their own devices.
Once you've created an interface, you can permanently host your interface on Huggingface Spaces. Huggingface Spaces will host the interface on its servers and provide you with a link you can share.
Gradio is now an essential part of our ML demos. All it takes is a few minutes to make a demo come to life.
Gradio accelerated our efforts to build and demo interdisciplinary models by quickly letting clinicians interact with machine learning models without writing any code. It's a huge time-saver!
