pingzhili/flashmd-mace-mp-0-medium

MACE-MP-0 medium for FlashMD

The MACE-MP-0 medium foundation model (MACE-MP-0a, 2023-12-03, 4,688,656 parameters) converted to the neutral format that FlashMD reads without mace-torch, e3nn or cuEquivariance. The trained weights are unchanged; this repository only re-packages them.

Files

• tensors.pt: a flat dict of float64 tensors, loadable with torch.load(path, weights_only=True): every trained weight plus the constants the network needs (Clebsch-Gordan coefficients of each tensor product path, the U matrices of the symmetric contractions, the real spherical harmonics as monomial coefficients).
• config.json: architecture, irreps, path normalizations, tensor names and provenance. tensors_sha256 is the SHA-256 of tensors.pt.

Use

import flashmd

model = flashmd.load("mace-mp-0-medium")  # downloads this repository

Provenance

• Original file: 2023-12-03-mace-128-L1_epoch-199.model from https://github.com/ACEsuit/mace-mp/releases/tag/mace_mp_0, SHA-256 01bfe22100139f424713cf921144e5509cbe353d67aa9fa1be9c6e1e0ed35845.
• Converted with references/mace/export.py of FlashMD (mace-torch 0.3.17, e3nn 0.4.4, torch 2.10.0). Every constant is checked against the official modules before it is written.
• tensors.pt SHA-256: e26ee7edd0650c398f626163ee4b4038e337515169947fda451182969ca05686.

License and citation

The MACE-MP-0 models are released by their authors under the MIT license (see the model table of https://github.com/ACEsuit/mace-foundations); this conversion is distributed under the same license, reproduced below. Please cite the original work:

I. Batatia et al., "A foundation model for atomistic materials chemistry", arXiv:2401.00096 (2023).

MIT License

Copyright (c) 2024 MACE-MP

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