containers/omlmd
OCI Artifact for ML model & metadata
This project helps MLOps engineers and machine learning developers package, distribute, and manage trained machine learning models along with their crucial metadata. It takes a model file and its associated details (like author, license, and performance metrics) and organizes them into a standardized container format. The output is a portable, versioned ML artifact that can be easily pushed to and pulled from container registries.
Available on PyPI.
Use this if you need a standardized and robust way to store, share, and retrieve your machine learning models and their associated metadata across different environments.
Not ideal if you are looking for a platform to train models, orchestrate ML pipelines, or manage the entire MLOps lifecycle beyond artifact management.
Stars
79
Forks
7
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 09, 2026
Commits (30d)
0
Dependencies
4
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