Building Interactive Applications with Gradio Spaces
Last updated July 1, 2024
Introduction: Gradio is an open-source Python library that allows you to quickly create customizable user interfaces for your machine learning models. Gradio Spaces on Hugging Face enable you to deploy these interfaces on the web, making your models accessible to users interactively.
Steps:
- Install Gradio
- Ensure Gradio is installed in your environment
2.Create a Basic Gradio Interface
- Define the Interface: import gradio as gr from transformers import pipeline model = pipeline('sentiment-analysis') defsentiment_analysis(text): return model(text) iface = gr.Interface(fn=sentiment_analysis, inputs="text", outputs="label") iface.launch()
- Deploy Your Interface on Hugging Face Spaces
- Sign in to Hugging Face and create a new Space:
- Go to the Hugging Face Spaces and create a new Space.
- Choose Gradio as the SDK
Push Your Code to the Space:
bash
Copy code
git init
git add .
git commit -m "Initial commit" git remote add origin https://huggingface.co/spaces/your_username/your_space_name
git push -u origin main
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