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.
PhACE	SO(3)-equivariant message-passing model with physical radial functions and fast tensor products.
GAP	Sparse Gaussian Approximation Potential (GAP) using Smooth Overlap of Atomic Positions (SOAP).
FlashMD	An architecture for the direct prediction of molecular dynamics