Stability

Stability#

We’re going to start simple here - let’s run a local relaxation (optimize the unit cell and positions) using a pre-trained EquiformerV2-31M-OMAT24-MP-sAlex checkpoint. This checkpoint has a few fun properties

  1. It’s a relatively small (31M) parameter model

  2. It was pre-trained on the OMat24 dataset, and then fine-tuned on the MPtrj and Alexandria datasets, so it should emit energies and forces that are consistent with the MP GGA (PBE/PBE+U) level of theory

This code will download the appropriate checkpoint from huggingface_hub automatically; if you don’t have the right access token specified, you’ll hit an permission or 401 error.

import pprint

from ase.build import bulk
from ase.optimize import LBFGS
from quacc.recipes.mlp.core import relax_job

# Make an Atoms object of a bulk Cu structure
atoms = bulk("Cu")

# Run a structure relaxation
result = relax_job(
    atoms,
    method="fairchem",
    model_name="EquiformerV2-31M-OMAT24-MP-sAlex",
    local_cache="./fairchem_checkpoint_cache/",
    opt_params={"fmax": 1e-3, "optimizer": LBFGS},
)

pprint.pprint(result)

Congratulations; you ran your first relaxation using an OMat24-trained checkpoint and quacc!