Hosting ML demos on Hugging Face Spaces with Streamlit

AI Impact Summary

Hugging Face Spaces now enables hosting Streamlit-based demos of Hugging Face models and datasets, turning model UIs into shareable web apps. The post demonstrates loading Hugging Face models, building interfaces with Streamlit widgets (text_area, sliders, dataframes) and serving them in Spaces, and using the datasets library with streaming to visualize large corpora (e.g., poetry). This reduces time-to-market for demos and stakeholder reviews, and helps teams showcase capabilities without bespoke infrastructure, while raising considerations around dependency alignment (requirements.txt) and ensuring the Spaces runtime matches local Streamlit versions.