mlcommons/ck-mlops

A collection of portable workflows, automation recipes and components for MLOps in a unified CK format. Note that this repository is outdated - please check the 2nd generation of the CK workflow automation meta-framework with portable MLOps and DevOps components here:

38
/ 100
Emerging

This collection of tools helps machine learning engineers and MLOps practitioners automate the often-complex process of benchmarking, optimizing, and deploying machine learning models. It takes in various ML models, datasets, and frameworks, and outputs performance benchmarks, optimized configurations, and deployable ML systems that work across different hardware and software environments. It's designed for professionals managing the lifecycle of ML systems.

No commits in the last 6 months.

Use this if you need to standardize and automate the benchmarking, optimization, and deployment of your ML models across diverse platforms and environments.

Not ideal if you are looking for the latest generation of this framework, as this specific repository is outdated.

MLOps ML System Deployment Performance Benchmarking Model Optimization ML Workflow Automation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 16 / 25

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Stars

19

Forks

7

Language

Python

License

Apache-2.0

Last pushed

Dec 10, 2024

Commits (30d)

0

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