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| title: AceFF-2 ML Potential Explorer | |
| emoji: ⚛️ | |
| colorFrom: purple | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 6.30.0 | |
| app_file: app.py | |
| short_description: Energy, forces & relaxation with the AceFF-2 ML potential | |
| python_version: "3.12" | |
| startup_duration_timeout: 30m | |
| license: apache-2.0 | |
| # AceFF-2 — Machine Learning Potential for Small Molecules | |
| Interactive demo for [AceFF](https://huggingface.co/papers/2601.00581) | |
| (*"AceFF: A State-of-the-Art Machine Learning Potential for Small Molecules"*, | |
| Acellera), a neural interatomic potential for drug-like molecules built on the | |
| **TensorNet v2** architecture in [TorchMD-Net](https://github.com/torchmd/torchmd-net). | |
| ## What it does | |
| - **Input** a small molecule as an **XYZ block**, **PDB**, or **SMILES** | |
| (SMILES gets a 3D geometry embedded with RDKit). | |
| - Set the **net charge** (−2…+2) and pick a checkpoint: | |
| [AceFF-2.0](https://huggingface.co/Acellera/AceFF-2.0) or | |
| [AceFF-2-OMOL](https://huggingface.co/Acellera/AceFF-2-OMOL) (adds Na, K). | |
| - **Single point**: potential energy (eV and kcal/mol) and per-atom forces | |
| (eV/Å), visualized as force arrows on an interactive 3Dmol.js viewer. | |
| - **Relax**: optionally minimize the geometry with ASE's LBFGS at the AceFF-2 | |
| potential and download the relaxed XYZ. | |
| Supported elements: H, B, C, N, O, F, Si, P, S, Cl, Br, I (AceFF-2.0) or with | |
| Na, K (OMOL). Small molecules only. Model and code are Apache-2.0 / MIT | |
| licensed. Example molecules are taken from the Acellera usage docs | |
| (caffeine, aspirin, acetate) — geometries embedded locally with RDKit. |