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README.md

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+---
+pipeline_tag: other
+---
+
+# DyneTrion: Spatiotemporally Coherent Generative Emulation of Protein Dynamics Across Timescales
+
+This repository contains the pretrained weights for **DyneTrion**, a generative protein dynamics emulator that jointly enforces geometric symmetry, structural consistency, and temporal coherence within a single framework.
+
+- **Paper:** [DyneTrion: A Spatio-temporally Coherent Generative Emulator for Protein Dynamics Across Timescales](https://huggingface.co/papers/2607.15309)
+- **GitHub Repository:** [fudan-generative-vision/DyneTrion](https://github.com/fudan-generative-vision/DyneTrion)
+
+<table class="center">
+  <tr>
+    <td style="text-align: center"><b>1ail_A</b></td>
+    <td style="text-align: center"><b>1ifg_A</b></td>
+    <td style="text-align: center"><b>2kxl_A</b></td>
+    <td style="text-align: center"><b>2rcs_H</b></td>
+  </tr>
+  <tr>
+    <td style="text-align: center">
+      <img src="https://raw.githubusercontent.com/fudan-generative-vision/DyneTrion/main/assets/1ail_A.gif" width="100%">
+    </td>
+    <td style="text-align: center">
+      <img src="https://raw.githubusercontent.com/fudan-generative-vision/DyneTrion/main/assets/1ifg_A.gif" width="100%">
+    </td>
+    <td style="text-align: center">
+      <img src="https://raw.githubusercontent.com/fudan-generative-vision/DyneTrion/main/assets/2kxl_A.gif" width="100%">
+    </td>
+    <td style="text-align: center">
+      <img src="https://raw.githubusercontent.com/fudan-generative-vision/DyneTrion/main/assets/2rcs_H.gif" width="100%">
+    </td>
+  </tr>
+</table>
+
+## Installation
+
+```bash
+# Create virtual environment (Python 3.10.12 is recommended)
+python -m venv .venv
+source .venv/bin/activate
+
+# Install PyTorch (CUDA 12.4)
+pip install torch==2.4.0 --index-url https://download.pytorch.org/whl/cu124
+
+# Install other dependencies
+pip install -r requirements.txt
+```
+
+## Inference
+
+Run inference using:
+
+```bash
+bash inference.sh
+```
+
+- Model checkpoint: `step_400000.pth`
+- Input CSV: `datasets/inference/inference_data.csv`
+- Frame number: `n_frame = 16`
+- Motion number: `n_motion = 2`
+- Frame sampling step: `sample_step = 40`
+- Extrapolation time: `extrapolation_time = 16`
+- Noise scale: `noise_scale = 1.0`
+
+Inference results will be saved to `save_root` (default: `./test/inference/`).
+
+For more details, please check the [GitHub Repository](https://github.com/fudan-generative-vision/DyneTrion).
+
+## Citation
+
+If you find DyneTrion useful for your research, please cite the paper:
+
+```bibtex
+@article{cheng2025dynetrion,
+  title={DyneTrion: A Spatio-temporally Coherent Generative Emulator for Protein Dynamics Across Timescales},
+  author={Cheng, Kaihui and Cai, Zhiqiang and Tu, Peng and Yao, Yisong and Han, Limei and Wu, Libo and Zhu, Siyu and Yang, Tzuhsiung and Qi, Yuan},
+  journal={arXiv preprint arXiv:2607.15309},
+  year={2026}
+}
+```