Run the following commands to install the required packages:
./setup_env.sh
Note: if working on sherlock make sure to download the correct modules before running the above command.
ml python/3.9.0 && ml gcc/10.1.0 && ml cudnn/8.9.0.131 && ml load cuda/12.4.1
- Train S5 model on sequential CIFAR10
python -m example --grayscale
- Train a GRU model on the Brain Computer Interface (BCI) dataset from Willett et al. 2023.
1. Download data in directory and export directory path to the environment variable $DEEP_SSM_DATA
gsutil cp gs://cfan/interspeech24/brain2text_competition_data.pkl .
export DEEP_SSM_DATA=/path/to/data
Note: on sherlock the data is already available in the following directory:
export DEEP_SSM_DATA=/scratch/groups/swl1
2. Run code to debug model:
python run.py --config-name="baseline_gru" trainer_cfg.fast_dev_run=1
3. Full code to train mode: python run.py --config-name="baseline_gru"
python run.py --config-name="baseline_gru"
- Train a Mamba model on the Brain Computer Interface (BCI) dataset from Willett et al. 2023
python run.py --config-name="baseline_mamba"