Gradio AI Web Application - Hands-On Python Example With JoJoGAN Face Stylization Model

Learn how to deploy a machine learning model using the Python Gradio library in Google Colab with this hands-on tutorial. Explore the process of implementing the JoJoGAN face style transfer model, covering topics such as setting up JoJoGAN in Colab, copying models, writing inference code as a function, converting GPU tensors to CPU numpy arrays, creating a Gradio app interface, launching the app, and testing it as a public link. Gain practical experience in ML model deployment and web application development while working with cutting-edge face stylization technology.

- Video Starts
- Video Content Review
- What is covered?
- Why Gradio?
- Setting JoJoGAN in Colab
- Copying models to Colab
- Inference code as function
- GPU Tensor to CPU numpy conversion
- Python gradio app interface
- Python gradio app launch
- Testing app in as public link
- Export notebook to GitHub