MLOps packaging: HuggingFace and GitHub Container Registry

Learn how to package a #HuggingFace GPT2 model using automation with #MLOps and pushing the result to GitHub Container Registry. With just a little bit of #Python and #FastAPI you can have a powerful text generation API that is self-documented! ▬▬🥇 Learn Objectives ▬▬ 🚀 Create a FastAPI application with HuggingFace 🚀 Interact with the model with HTTP from a container using FastAPI 🚀 Containerize the application using GitHub Actions 🚀 Create repository secrets to login and push to GitHub Container Registry ▬▬ C H A P T E R S ⏰ ▬▬ 00:00 Introduction 00:25 Project Overview 03:00 Build Container 04:40 Run container locally 06:43 GitHub Action workflow 09:15 Azure Container Registry 09:35 GitHub Action workflow 10:11 Commit and trigger action 12:00 Verify image is on GitHub Container registry ▬▬ 🔗 R E S O U R C E S ▬▬ Example repository → https://github.com/alfredodeza/huggingface-ghcr Practical MLOps book → https://www.amazon.com/Practical-MLOps-Operationalizing-Machine-Learning/dp/1098103017/ Packaging ML models → https://learning.oreilly.com/videos/packaging-machine-learning/50116VIDEOPAIML/