export CUDA_VISIBLE_DEVICES=4
# or use multi-gpu training when you want:
# export CUDA_VISIBLE_DEVICES=0,1
model=bridge_if_esm1b_650m_pifold_gym
exp=fixedbb/${model}
dataset=gym
name=fixedbb/mutdpo/${model}/0_515


python ./train.py \
    experiment=${exp} datamodule=${dataset} name=${name} \
    task.generator.diffusion_steps=25 \
    datamodule.cvfold_index=0 \
    logger=wandb trainer=ddp_fp16