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AI and ML workflows module for scientific digital twins.

Project description

GitHub Super-Linter GitHub Super-Linter SQAaaS source code

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itwinai is a Python toolkit designed to help scientists and researchers streamline AI and machine learning workflows, specifically for digital twin applications. It provides easy-to-use tools for distributed training, hyper-parameter optimization on HPC systems, and integrated ML logging, reducing engineering overhead and accelerating research. Developed primarily by CERN, in collaboration with Forschungszentrum Jülich (FZJ), itwinai supports modular and reusable ML workflows, with the flexibility to be extended through third-party plugins, empowering AI-driven scientific research in digital twins.

See the latest version of our docs here.

Installation

For instructions on how to install itwinai, please refer to the user installation guide or the developer installation guide, depending on whether you are a user or developer

For information about how to use containers or how to test with pytest, you can look at the following documents:

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