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fennol-tools/FeNNix-Bio1
FeNNix-Bio1 is a machine learning model from fennol-tools. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
An efficient machine-learning interatomic potential for molecular dynamics simulations of organic and biological systems trained on an extension of the SPICE2 dataset. The model comes in two sizes (S and M).
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Updated Jan 13, 2026
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From the Hugging Face model README
An efficient machine-learning interatomic potential for molecular dynamics simulations of organic and biological systems trained on an extension of the SPICE2 dataset. The model comes in two sizes (S and M).
Developed by: T. Plé, O. Adjoua, A. Benali, E. Posenitskiy, C. Villot, L. Lagardère and J.-P. Piquemal
License: Academic Software License (ASL)
Repository: github.com/FeNNol-tools/FeNNol-PMC/tree/main/FENNIX-BIO1
Download one of the models from github.com/FeNNol-tools/FeNNol-PMC/tree/main/FENNIX-BIO1. Install the FeNNol library
pip install fennol[cuda]
The model can easily be used with ASE:
from fennol.ase import FENNIXCalculator
import sys
from ase import Atoms
from ase.md.verlet import VelocityVerlet
from ase.io import read
from ase import units
import time
xyz_file = sys.argv[1]
atoms = read(xyz_file)
calc = FENNIXCalculator(model="fennix-bio1M.fnx", gpu_preprocessing=True)
atoms.calc = calc
dyn = VelocityVerlet(atoms, 1.0 * units.fs) # 1 fs time step
nsteps = 100_000
steps_per_print = 100
t0 = time.time()
for step in range(1,nsteps+1):
dyn.run(1)
if step % steps_per_print == 0:
t1 = time.time()
steps_per_second = steps_per_print / (t1 - t0)
print(f"Step: {step:10}, Energy: {atoms.get_potential_energy():15.5f} eV, Steps/s: {steps_per_second:.2f}")
t0 = time.time()
For better performance, we recommend directly using FeNNol's MD engine (see the example directory in FeNNol's github repo)
Plé T, Adjoua O, Benali A, Posenitskiy E, Villot C, Lagardère L, Piquemal J-P A Foundation Model for Accurate Atomistic Simulations in Drug Design. ChemRxiv. 2025; doi:10.26434/chemrxiv-2025-f1hgn-v4
BibTeX:
@article{Ple-2025,
title={A Foundation Model for Accurate Atomistic Simulations in Drug Design},
DOI={10.26434/chemrxiv-2025-f1hgn-v4},
journal={ChemRxiv},
author={Plé, Thomas and Adjoua, Olivier and Benali, Anouar and Posenitskiy, Evgeny and Villot, Corentin and Lagardère, Louis and Piquemal, Jean-Philip},
year={2025}
}