metatrain is a command line interface (CLI) to train and evaluate atomistic models of various architectures. It features a common yaml option inputs to configure training and evaluation. Trained models are exported as standalone files that can be used directly in various molecular dynamics (MD) engines (e.g. ASE, LAMMPS, i-PI, TorchSim, ESPResSo,…) using the metatomic interface.

The idea behind metatrain is to have a general training hub that provides a homogeneous environment and user interface, transforming every ML architecture into an end-to-end model that can be connected to MD engines. Any custom architecture compatible with TorchScript can be integrated into metatrain, gaining automatic access to a training and evaluation interface, as well as compatibility with various MD engines.

List of Implemented Architectures

Currently metatrain supports the following architectures for building an atomistic model:

Name	Description
PET	Point Edge Transformer (PET), interatomic machine learning potential
SOAP-BPNN	A Behler-Parrinello neural network with SOAP features
MACE	A higher order equivariant message passing neural network.
GAP	Sparse Gaussian Approximation Potential (GAP) using Smooth Overlap of Atomic Positions (SOAP).
FlashMD	An architecture for the direct prediction of molecular dynamics