Boltz-2 weights (tt-bio mirror)
Mirror of the Boltz-2 structure- and
affinity-prediction weights, packaged for use with
tt-bio on Tenstorrent hardware. The
files are byte-for-byte identical to the upstream Boltz-2 release; this repo
simply hosts them on the Hugging Face Hub so tt-bio can fetch them with
huggingface_hub like every other model it runs.
Files
| File | Description |
|---|---|
boltz2_conf.ckpt |
Boltz-2 structure / confidence model |
boltz2_aff.ckpt |
Boltz-2 binding-affinity model |
mols.tar |
CCD molecule / component library used during featurization |
Usage
tt-bio downloads these automatically:
tt-bio predict examples/prot.yaml --model boltz2 --use_msa_server --override
Or fetch a single file directly:
from huggingface_hub import hf_hub_download
path = hf_hub_download("moritztng/boltz-2", "boltz2_conf.ckpt")
Credit & license
Boltz-2 is developed by Jeremy Wohlwend, Gabriele Corso, Saro Passaro and the
Boltz authors (MIT Jameel Clinic) and released under the MIT License. The
weights and the accompanying LICENSE are redistributed here unmodified under
those same terms. See the upstream project at
https://github.com/jwohlwend/boltz and please cite the Boltz-2 work if you
use these weights.