Garden's Almanac of Matter Models

Orb-v2

January 2024

Checkpoint Params Polaris Sophia Perlmutter Delta Frontier Della
orb-v2 25M
orb-d3-v2 25M
orb-mptraj-only-v2 25M
verified, last 30 days installed, not recently verified not installed

No cluster has installed any checkpoint of this model yet.


Running this model
1# from a job or interactive session on a supported cluster:
2from rootstock import RootstockCalculator
3
4with RootstockCalculator(
5 cluster=YOUR_CLUSTER_ID, # eg, "delta", "frontier"
6 checkpoint="orb-v2",
7 device="cuda",
8) as calc:
9 # model is now running in subprocess on compute node
10 atoms.calc = calc
11 atoms.get_potential_energy()

Environments

Rootstock runs each model family inside an isolated Python environment defined by a single file. This environment file includes the specific dependencies needed, plus a setup() function that loads the model and returns an ASE calculator. These files are usually almost identical for a given model family, but because of cluster-specific quirks (eg, an old CUDA driver) the dependencies and setup code can vary a bit.

orb_env.py
1# /// script
2# requires-python = ">=3.10"
3# dependencies = [
4# "orb-models>=0.4.0",
5# "ase>=3.22",
6# "torch>=2.0",
7# ]
8# ///
9"""Orb env — hosts Orbital Materials' Orb universal potentials."""
10
11CHECKPOINTS = {
12 "orb-v2": "orb-v2",
13}
14
15
16def setup(checkpoint: str, device: str = "cuda"):
17 import torch
18 from orb_models.forcefield import pretrained
19 from orb_models.forcefield.calculator import ORBCalculator
20
21 # orb-models exposes one function per checkpoint, e.g. pretrained.orb_v2().
22 fn_name = CHECKPOINTS[checkpoint].replace("-", "_")
23 load_fn = getattr(pretrained, fn_name)
24 orbff = load_fn(device=torch.device(device))
25 return ORBCalculator(orbff, device=torch.device(device))
26

Built on Polaris: 2026-05-12

Couldn't load the current environments from Rootstock.


References
  1. Neumann, Mark, Gin, James, Rhodes, Benjamin, Bennett, Steven, Li, Zhiyi, Choubisa, Hitarth, Hussey, Arthur, Godwin, Jonathan, Orb: A Fast, Scalable Neural Network Potential, arXiv, 2024.