Metadata-Version: 2.4
Name: metatomic
Version: 0.1.0
Summary: Atomistic machine learning models you can use everywhere for everything
Author: Guillaume Fraux, Filippo Bigi
License-Expression: BSD-3-Clause
Project-URL: homepage, https://docs.metatensor.org/metatomic/
Project-URL: documentation, https://docs.metatensor.org/metatomic/
Project-URL: repository, https://github.com/metatensor/metatomic
Keywords: machine learning,molecular modeling
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
License-File: LICENSE
License-File: AUTHORS
Provides-Extra: torch
Requires-Dist: metatomic-torch; extra == "torch"
Dynamic: author
Dynamic: license-file
Dynamic: provides-extra

<h1>
<p align="center">
    <img src="https://raw.githubusercontent.com/metatensor/metatomic/refs/heads/main/docs/static/images/metatomic-horizontal-dark.png" alt="Metatomic logo" width="600"/>
</p>
</h1>

<h4 align="center">

[![tests status](https://img.shields.io/github/checks-status/metatensor/metatomic/main)](https://github.com/metatensor/metatomic/actions?query=branch%3Amain)
[![documentation](https://img.shields.io/badge/documentation-latest-sucess)](https://docs.metatensor.org/metatomic/)
[![coverage](https://codecov.io/gh/metatensor/metatomic/branch/main/graph/badge.svg)](https://codecov.io/gh/metatensor/metatomic)
</h4>


``metatomic`` is a library that defines a common interface between atomistic
machine learning models, and atomistic simulation engines. Our main goal is to
define and train models once, and then be able to re-use them across many
different simulation engines (such as LAMMPS, GROMACS, *etc.*). We strive to
achieve this goal without imposing any structure on the model itself, and to
allow any model architecture to be used.


## Documentation

For details, tutorials, and examples, please have a look at our
[documentation](https://docs.metatensor.org/metatomic/).


## Contributors

Thanks goes to all people that make metatensor possible:

[![contributors list](https://contrib.rocks/image?repo=metatensor/metatomic)](https://github.com/metatensor/metatomic/graphs/contributors)

We always welcome new contributors. If you want to help us take a look at our
[contribution guidelines](CONTRIBUTING.rst) and afterwards you may start with an
open issue marked as [good first
issue](https://github.com/metatensor/metatomic/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22).
