| --- |
| license: other |
| license_name: mixed |
| license_link: LICENSE.md |
| library_name: safetensors |
| tags: [interatomic-potential, chemistry, materials, webgpu] |
| --- |
| |
| # Models for MLIP-Visualization |
|
|
| Converted weights for [MLIP-Visualization](https://github.com/EricBoittier/MLIP-Visualization), |
| which runs machine-learning interatomic potentials in the browser and draws every forward and |
| backward pass. The app downloads these files directly; they are plain safetensors plus a JSON |
| file of hyperparameters per model. |
|
|
| | file | model | source | licence | |
| |---|---|---|---| |
| | `pet-mad-xs` | PET-MAD XS | lab-cosmo/upet, converted with convert_pet.py | BSD-3-Clause | |
| | `mace-mp-0b3-medium` | MACE-MP-0b3 medium | mace-foundations/mace-mp-0, converted with convert_mace.py | MIT | |
| | `mace-mp-0b2-small` | MACE-MP-0b2 small | mace-foundations/mace-mp-0, converted with convert_mace.py | MIT | |
| | `lorem-demo` | LOREM demo | metatrain experimental LOREM, random initialization from convert_lorem.py | MIT | |
| | `ani-2x` | ANI-2x | TorchANI models.ANI2x(), converted with convert_ani.py | MIT | |
| | `physnet-acetone` | PhysNet · acetone MP2 | mmml physnetjax, trained with train_physnet_demo.py | MIT | |
| | `pet-mols-s-v1.0` | PET-MOLS S v1.0 | lab-cosmo/upet, converted with convert_pet.py | BSD-3-Clause | |
|
|
| `index.json` lists what the app offers. |
|
|
| ## Credits |
|
|
| - **PET-MAD / PET-MOLS**: [lab-cosmo/upet](https://huggingface.co/lab-cosmo/upet) (BSD-3-Clause), converted with |
| [pet-kokkos](https://github.com/EricBoittier/pet-kokkos)'s `convert_pet.py`. Cite the PET and PET-MAD papers when you use them. |
| - **MACE-MP-0**: [mace-foundations/mace-mp-0](https://huggingface.co/mace-foundations/mace-mp-0) (MIT), Batatia et al., |
| *A foundation model for atomistic materials chemistry* (2023), converted with `scripts/convert_mace.py`. |
| - **LOREM demo**: a random initialization of [metatrain](https://github.com/lab-cosmo/metatrain)'s experimental LOREM |
| (Bigi et al., arXiv:2507.19382), exported with `scripts/convert_lorem.py`. Not a trained potential. |
| - **ANI-2x**: [TorchANI](https://github.com/aiqm/torchani) (MIT), Devereux et al., *J. Chem. Theory Comput.* 16, 4192 (2020), |
| converted with `scripts/convert_ani.py`. |
| - **PhysNet (acetone)**: a small invariant PhysNet ([mmml](https://github.com/EricBoittier/mmml) `physnetjax`, MIT, |
| max_degree = 0) trained for this app on mmml's acetone-dimer MP2 example data, with `scripts/train_physnet_demo.py`. |
| |
