⚙️ artifact-experiment

Declarative builder toolkit for reusable validation workflows with integrated tracking.

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📋 Overview

artifact-experiment constitutes the experiment orchestration extension to Artifact-ML.

It provides tools to build reusable validation workflows with integrated tracking.

It stands alongside:

artifact-core: a declarative interface for the computation of validation artifacts in ML experiments.
artifact-torch: PyTorch integration for building reusable deep-learning workflows declaratively.

🚀 Installation

Install the latest release from PyPI by running:

pip install artifact-experiment

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

📚 Documentation

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

🤝 Contributing

Contributions are welcome!

Please consult our contribution guidelines document.

📄 License

This project is licensed under the MIT License.

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