#!/bin/bash #SBATCH --job-name=caption-test #SBATCH --partition=a4000 #SBATCH --gres=gpu:1 # GPU »ç¿ë #SBATCH --time=10-04:30:00 # ÃÖ´ë ½ÇÇà ½Ã°£ (10ÀÏ 4½Ã°£ 30ºÐ) #SBATCH --mem=10G # ¸Þ¸ð¸® (10GB) #SBATCH --cpus-per-task=4 # CPU ÄÚ¾î ¼ö #SBATCH --output=logs/gpt_ref-ytvos_numbered_cy_sanity.log # Ãâ·Â ·Î±× ÀúÀå °æ·Î # ȯ°æ ¼³Á¤ ml purge ml load cuda/11.8 eval "$(conda shell.bash hook)" conda activate risall # Python ½ºÅ©¸³Æ® ½ÇÇà python ./mbench/gpt_ref-ytvos_numbered_cy_sanity_2.py --save_caption_path "mbench/numbered_captions_gpt-4o_nomask_randcap2.json" \ --save_valid_obj_ids_path "mbench/numbered_valid_obj_ids_gpt-4o_nomask_randcap2.json" # #!/bin/bash # #SBATCH --job-name=jupyter # #SBATCH --partition=a4000 # ????? ???? ????: a6000 or a100 # #SBATCH --gres=gpu:0 # Use 1 GPU # #SBATCH --time=10-04:30:00 # d-hh:mm:ss ????, ???? job?? max time limit ???? # #SBATCH --mem=3G # cpu memory size # #SBATCH --cpus-per-task=3 # cpu ???? # #SBATCH --output=jptr_chaeyun.txt # ?????? ???? ??? std output?? ?????? ???? ??? # ml purge # ml load cuda/11.8 # eval "$(conda shell.bash hook)" # conda activate risall # # python datagen.py # srun jupyter notebook --no-browser --port=5727