# About

Over the years, Météo-France's AILab has gathered reusable code for meteorological machine learning applications in its `mfai` library. It contains a variety of PyTorch neural network architectures (CNNs, Vision Transformers, small LLMs, small multimodal LMs, etc.), a `NamedTensor` class, losses, metrics, and PyTorch Lightning training strategies.

All the elements of the mfai library are implemented from research papers and have been improved, tested, and proven to work in real-world operational meteorological applications at Météo-France.

`mfai` is not a framework, but it provides elements to use in your preferred one.


## Citation
If you use this library in your research project, please cite it as below.
```
Météo-France, Berthomier L., Dewasmes O., Guibert F., Pradel B., Tournier T. mfai URL: https://github.com/meteofrance/mfai
```


# Acknowledgements

This package is maintained by the AI Lab team at Météo-France. We would like to thank the authors of the papers and codes we used to implement the models (see [above links](#neural-network-architectures) to **arxiv** and **github**) and the authors of the libraries we use to build this package (see our [**requirements.txt**](https://github.com/meteofrance/mfai/blob/main/requirements.txt)).