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Spaces

Spaces are interactive machine learning applications that can be shared and used directly in the browser. This section provides guides on creating, deploying, and managing Spaces using different frameworks like Gradio and Streamlit.

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Deploying Streamlit Applications on Hugging Face

Last updated July 1, 2024

Introduction: Streamlit is a powerful and easy-to-use framework for creating interactive web applications with Python. Hugging Face Spaces support deploying Streamlit apps, allowing you to share interactive models and visualizations effortlessly.

Steps:

Install Streamlit

Ensure Streamlit is installed pip install streamlit

2.Create a Basic Streamlit App

Example App Code import streamlit as st from transformers import pipeline st.title('Sentiment Analysis with Hugging Face') model = pipeline('sentiment-analysis') user_input = st.text_area("Enter text for sentiment analysis:") if st.button('Analyze'): result = model(user_input) st.write(result)

3.Deploy Your Streamlit App on Hugging Face Spaces

Set Up Your Space:

Push Your 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

4.Customize Your Streamlit App

Add Widgets and Visualizations

import matplotlib.pyplot as plt import numpy as np st.title('Interactive Data Visualization') x = np.linspace(0, 10, 100) y = np.sin(x) fig, ax = plt.subplots() ax.plot(x, y) st.pyplot(fig)

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