Download webLigandMPNN/README.md from MurrellLab/webports: direct link, hf CLI and curl.
- Browser
- Download file 1.52 kB
-
https://huggingface.co/MurrellLab/webports/resolve/main/webLigandMPNN/README.md
- Command line
-
hf download hf://MurrellLab/webports/webLigandMPNN/README.md
-
curl -L -o README.md https://huggingface.co/MurrellLab/webports/resolve/main/webLigandMPNN/README.md
webLigandMPNN model assets
Browser-ready ONNX bundles for the unofficial
webLigandMPNN port. These
files were converted from checkpoints trained and released by the original
dauparas/LigandMPNN authors.
MurrellLab performed the web conversion and did not train the models.
Layout
models/ contains four LigandMPNN sequence models and the learned side-chain
packer:
ligandmpnn_v_32_005_25ligandmpnn_v_32_010_25(default sequence model)ligandmpnn_v_32_020_25ligandmpnn_v_32_030_25ligandmpnn_sc_v_32_002_16(side-chain packer)
Each directory is a self-contained web bundle. manifest.json lists the files
needed at runtime and records their sizes and SHA-256 hashes. Additional parity
and validation JSON files document the conversion checks. catalog.json
indexes every hosted file and its digest. No original PyTorch .pt checkpoint
is included.
Provenance and licenses
upstream.lock.json pins upstream LigandMPNN revision
26ec57ac976ade5379920dbd43c7f97a91cf82de and records the original checkpoint
hashes and source URLs without redistributing those checkpoint files. The
LigandMPNN license is included in every bundle. The packing bundle also retains
the Apache-2.0 license and notice for geometry derived from OpenFold constants.
See THIRD_PARTY_NOTICES.md and the source repository documentation for full
attribution, validation scope, API usage, and scientific limitations.