Artifact-ML foundation: a declarative interface for the computation of validation artifacts in ML experiments.
Project description
⚙️ artifact-core
A declarative interface for the computation of validation artifacts in ML experiments.
📋 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
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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