⚙️ artifact-core

A declarative interface for the computation of validation artifacts in ML experiments.

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📋 Overview

artifact-core constitutes the foundation of Artifact-ML.

It provides a declarative interface for the computation of validation artifacts in ML experiments.

It stands alongside:

artifact-experiment: experiment orchestration extension for building reusable validation workflows with integrated tracking.
artifact-torch: PyTorch integration for building reusable deep-learning workflows declaratively.

🚀 Installation

Install the latest release from PyPI by running:

pip install artifact-core

To install from source (e.g. for development), consult the getting started guide.

📚 Documentation

Documentation for artifact-core is available at artifact-core docs.

🤝 Contributing

Contributions are welcome!

Please consult our contribution guidelines document.

📄 License

This project is licensed under the MIT License.

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