iterative/example-gto

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This helps data science teams track their machine learning models and their different versions across development, staging, and production environments. It takes your trained ML models and provides a clear overview of which model versions are active and where, enabling easier testing, sharing, and deployment. This is ideal for machine learning engineers and data scientists managing multiple models.

No commits in the last 6 months.

Use this if you need a clear, centralized way to see the status and version of all your machine learning models within your existing Git-based workflow.

Not ideal if you are looking for a visual, web-based dashboard with rich metrics and plots, as this tool primarily focuses on Git-native model versioning and promotion.

MLOps model-versioning model-lifecycle machine-learning-deployment data-science-workflow
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 17 / 25

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Last pushed

Sep 04, 2023

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