| --- |
| license: cc-by-nc-sa-4.0 |
| tags: |
| - MLIP |
| - MLFF |
| datasets: |
| - aixsim/Titan25 |
| --- |
| |
| # SNet-T25 |
| SNet-T25 is an MLIP trained on [Titan25 dataset](https://huggingface.co/datasets/aixsim/Titan25). |
| It was designed for general chemical reactivity, including interfacial reactions, |
| and trained on 1.8M data points across 11 elements (C, H, N, O, Ag, Au, Cu, Pd, Pt, Rh, Ru). |
| The evaluation results are available in [GAIA paper](https://arxiv.org/abs/2509.25798), |
| which also provides full details of the model architecture and hyperparameters. |
|
|
| The original SNet-T25 was trained with our in-house framework; |
| we provide a converted checkpoint that can be used directly with [SevenNet framework](https://github.com/MDIL-SNU/SevenNet). |
| To enable compatibility, the user only need to apply the following minor modifications: |
| - Modify line 5 in `SevenNet/sevenn/__init__.py` to, e.g., `__version__ = '0.11.0'`. This allows the user to use it without installing SevenNet. |
| - Comment out line 332 in `SevenNet/sevenn/checkpoint.py`, i.e., `assert len(missing) == 0, f'Missing keys: {missing}'` |
|
|
| # Citation |
| If using this checkpoint, please cite our work as follows: |
| ``` |
| @article{gaia2025, |
| title={Scalable Reactive Atomistic Dynamics with GAIA}, |
| author={Song, Suhwan and Kim, Heejae and Jang, Jaehee and Cho, Hyuntae and Kim, Gunhee and Kim, Geonu}, |
| journal={arXiv preprint arXiv:2509.25798}, |
| year={2025} |
| } |
| ``` |
