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MLOps packaging : HuggingFace and Docker.

O'Reilly Online Learning: Academic/Public Library Edition Available online

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Format:
Video
Contributor:
Deza, Alfredo, presenter.
Pragmatic AI Solutions (Firm), publisher.
Language:
English
Subjects (All):
Machine learning.
Computer software--Development.
Computer software.
Physical Description:
1 online resource (1 video file (16 min.)) : sound, color.
Edition:
[First edition].
Place of Publication:
[Place of publication not identified] : Pragmatic AI Solutions, [2022]
Summary:
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.
Notes:
OCLC-licensed vendor bibliographic record.
OCLC:
1334604734
Publisher Number:
50143VIDEOPAIML

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