An MLflow plugin that integrates DuckDB as a backend for artifact and model tracking, enabling efficient, serverless experiment management with a lightweight, portable database engine.
Project description
mlflow-duckdb
An MLflow plugin that enables logging and loading of artifacts and models using DuckDB as a lightweight, serverless backend for portable experiment tracking.
Overview
This is the initial release of mlflow-duckdb, published to reserve the package name on PyPI and lay the groundwork for future development.
The goal of this plugin is to integrate DuckDB with MLflow to support lightweight, local experiment tracking without requiring a server or cloud storage.
More features and documentation will be added in upcoming releases.
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