⚙️ artifact-torch
Declarative builder toolkit for reusable deep learning workflows.
📋 Overview
artifact-torch provides PyTorch integration for Artifact-ML.
It offers the tools to build reusable deep learning workflows declaratively.
It stands alongside:
artifact-core: a declarative interface for the computation of validation artifacts in ML experiments.artifact-experiment: experiment orchestration extension for building reusable validation workflows with integrated tracking.
🚀 Installation
Install the latest release from PyPI by running:
pip install artifact-torch
To install from source (e.g. for development, or to run the bundled demos), consult the getting started guide.
📚 Documentation
Documentation for artifact-torch is available at artifact-torch docs.
🤝 Contributing
Contributions are welcome!
Please consult our contribution guidelines document.
📄 License
This project is licensed under the MIT License.
1 maintainer
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