MLOps packaging : HuggingFace and Docker
- [Place of publication not identified] : Pragmatic AI Solutions, 
- [First edition].
- Physical Description:
- 1 online resource (1 video file (16 min.)) : sound, color
- Additional Creators:
- Deza, Alfredo and Pragmatic AI Solutions (Firm)
- MLOps packaging: HuggingFace and Docker Hub Use automation to package models Learn how to package a HuggingFace GPT2 model using automation with MLOps and pushing the result to Docker Hub. With just a little bit of Python and FastAPI you can have a powerful text generation API that is self-documented! Learn Objectives In this video lesson, I'll go over the details with an example repository you can use for reference including the following learning 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 Docker Hub Resources Example repository Practical MLOps book MLOps Maturity Model Packaging ML models.
- Sound Characteristics:
- Digital File Characteristics:
- video file
- Form of work:
- Instructional films
- Participant/Performer Note:
- Alfredo Deza, presenter.
View MARC record | catkey: 38359861