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Artifact-ML foundation: a unified interface for the declarative computation of validation artifacts in ML experiments.

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⚙️ artifact-core

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

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📋 Overview

artifact-core constitutes the foundation of Artifact-ML.

It provides a unified interface for the declarative computation of diverse 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

Clone the Artifact-ML monorepo by running:

git clone https://github.com/vasileios-ektor-papoulias/artifact-ml.git

Install the artifact-core package by running:

cd artifact-ml/artifact-core

poetry install

📚 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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