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README: remove 2 of three references to lightning-hydra-template, fix… #678

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11 changes: 1 addition & 10 deletions README.md
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# SchNetPack - Deep Neural Networks for Atomistic Systems
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/python/black)
[![](https://shields.io/badge/-Lightning--Hydra--Template-017F2F?style=flat&logo=github&labelColor=303030)](https://github.com/hobogalaxy/lightning-hydra-template)


SchNetPack is a toolbox for the development and application of deep neural networks to the prediction of potential energy surfaces and other quantum-chemical properties of molecules and materials. It contains basic building blocks of atomistic neural networks, manages their training and provides simple access to common benchmark datasets. This allows for an easy implementation and evaluation of new models.

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```

For more details on config groups, have a look at the
[Hydra docs](https://hydra.cc/docs/next/tutorials/basic/your_first_app/config_groups).
[Hydra docs](https://hydra.cc/docs/tutorials/basic/your_first_app/config_groups/).


### Example 2: Potential energy surfaces
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eprint = {https://doi.org/10.1021/acs.jctc.8b00908},
}



## Acknowledgements

CLI and hydra configs for PyTorch Lightning are adapted from this template: [![](https://shields.io/badge/-Lightning--Hydra--Template-017F2F?style=flat&logo=github&labelColor=303030)](https://github.com/hobogalaxy/lightning-hydra-template)


## References

* [1] K.T. Schütt. F. Arbabzadah. S. Chmiela, K.-R. Müller, A. Tkatchenko.
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