| #PBS -N gemma_finetuning_on_backdoor_data | |
| #PBS -l select=1:ncpus=16:mem=110G:ngpus=1 | |
| #PBS -l walltime=12:00:00 | |
| #PBS -j oe | |
| #PBS -k oe | |
| #PBS -o ${PBS_O_WORKDIR}/logs/multiple_layer_loss7_gpu_training_output.txt | |
| #PBS -P personal-maheep00 | |
| #PBS -q normal | |
| # Go to the directory where you submitted the job | |
| cd $PBS_O_WORKDIR | |
| # Initialize conda | |
| source ~/.bashrc | |
| # OR alternatively: source /opt/conda/etc/profile.d/conda.sh | |
| # Activate the conda environment | |
| conda activate safebymi | |
| python -m src.training.backdoor --model gemma --dataset spylab > safetynet/logs/gemma/training_on_backdoor_data.log 2>&1 | |