Building Data and Machine Learning Applications using Gradio
summary
Demos show Gradio and Streamlit UIs built pure Python apps (image-to-anime, Stable Diffusion inpainting, video classifier, StableLM chatbot, CSV defect predictor, Whisper transcription) that require no front-end code and load models from Hugging Face with one line of code via the Interface or Blocks APIs. Deployments use Hugging Face Spaces with automatic hosting, Docker templates and a FastAPI-style API endpoint; launch share=True opens an ngrok tunnel for easy sharing.
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chapters (22)
- 0:00Intro
- 0:36Background
- 2:25Example
- 3:02Stable Diffusion
- 3:32Anything is Possible
- 3:47Video Classifier
- 4:14StableLM
- 4:40Data Science Applications
- 5:18Whisper
- 5:52Interface
- 6:45Interface Example
- 8:20Example Input
- 8:40Blocks
- 9:40Blocks API
- 13:21SKOPS
- 13:58Deployment
- 14:52Examples
- 15:40APIs
- 16:50Docker Templates
- 17:20Getting Started
- 17:44Questions
- 22:02Gradio and Argilla
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