Quick Start#
The easiest way to use pretrained models is via the ASE FAIRChemCalculator
.
A single uma model can be used for a wide range of applications in chemistry and materials science by picking the
appropriate task name for domain specific prediction.
Instantiate a calculator from a pretrained model#
Make sure you have a Hugging Face account, have already applied for model access to the UMA model repository, and have logged in to Hugging Face using an access token.
Set the task for your application and calculate#
oc20: use this for catalysis
omat: use this for inorganic materials
omol: use this for molecules
odac: use this for MOFs
omc: use this for molecular crystals
Relax an adsorbate on a catalytic surface,
from ase.build import fcc100, add_adsorbate, molecule
from ase.optimize import LBFGS
from fairchem.core import pretrained_mlip, FAIRChemCalculator
predictor = pretrained_mlip.get_predict_unit("uma-sm", device="cuda")
calc = FAIRChemCalculator(predictor, task_name="oc20")
# Set up your system as an ASE atoms object
slab = fcc100("Cu", (3, 3, 3), vacuum=8, periodic=True)
adsorbate = molecule("CO")
add_adsorbate(slab, adsorbate, 2.0, "bridge")
slab.calc = calc
# Set up LBFGS dynamics object
opt = LBFGS(slab)
opt.run(0.05, 100)
Relax an inorganic crystal,
from ase.build import bulk
from ase.optimize import FIRE
from ase.filters import FrechetCellFilter
from fairchem.core import pretrained_mlip, FAIRChemCalculator
predictor = pretrained_mlip.get_predict_unit("uma-sm", device="cuda")
calc = FAIRChemCalculator(predictor, task_name="omat")
atoms = bulk("Fe")
atoms.calc = calc
opt = LBFGS(FrechetCellFilter(atoms))
opt.run(0.05, 100)
Run molecular MD,
from ase import units
from ase.io import Trajectory
from ase.md.langevin import Langevin
from ase.build import molecule
from fairchem.core import pretrained_mlip, FAIRChemCalculator
predictor = pretrained_mlip.get_predict_unit("uma-sm", device="cuda")
calc = FAIRChemCalculator(predictor, task_name="omol")
atoms = molecule("H2O")
atoms.calc = calc
dyn = Langevin(
atoms,
timestep=0.1 * units.fs,
temperature_K=400,
friction=0.001 / units.fs,
)
trajectory = Trajectory("my_md.traj", "w", atoms)
dyn.attach(trajectory.write, interval=1)
dyn.run(steps=1000)
Calculate a spin gap
from ase.build import molecule
from fairchem.core import pretrained_mlip, FAIRChemCalculator
predictor = pretrained_mlip.get_predict_unit("uma-sm", device="cuda")
# singlet CH2
singlet = molecule("CH2_s1A1d")
singlet.info.update({"spin": 1, "charge": 0})
singlet.calc = FAIRChemCalculator(predictor, task_name="omol")
# triplet CH2
triplet = molecule("CH2_s3B1d")
triplet.info.update({"spin": 3, "charge": 0})
triplet.calc = FAIRChemCalculator(predictor, task_name="omol")
triplet.get_potential_energy() - singlet.get_potential_energy()