artifact-torch 0.1.2

Artifact-ML PyTorch integration: declarative builder toolkit for reusable deep learning workflows.

⚙️ artifact-torch

Declarative builder toolkit for end-to-end, reusable deep learning workflows.

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📋 Overview

artifact-torch provides PyTorch integration for Artifact-ML.

It offers the tools to build reusable, end-to-end deep learning workflows declaratiely.

It stands alongside:

• artifact-core: a unified interface for the declarative computation of diverse validation artifacts in ML experiments.
• artifact-experiment: experiment orchestration extension for building reusable validation workflows with integrated tracking.

🚀 Installation

Clone the Artifact-ML monorepo by running:

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

Install the artifact-torch package by running:

cd artifact-ml/artifact-torch

poetry install

📚 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.