This project implements coordinate tokenization using Finite Scalar Quantization (FSQ) for molecular data.
The FSQ is currently implemented in the iFSQ version by default. If you want to switch to the standard FSQ:
- In
fsq.py, comment out lines 126 and 127. - Uncomment line 128.
This changes the activation from torch.sigmoid to torch.tanh in the symmetry-preserving bound.
-
Install dependencies:
pip install -r requirements.txt -
(Optional) Set up a conda environment or adjust paths as needed.
- Training: Adjust and run
submit_train.shorpython submit_train.py. - Evaluation: Adjust and run
python submit_eval.py --ckpt <checkpoint_path>.
- Adjust file paths (e.g., data directories, logs) for your environment.
- Ensure CUDA/GPU availability for training.