Download upstreams/flm/scripts/eval_owt_sedd.sh from jyliuAI/diffusion_baseline: direct link, hf CLI and curl.
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https://huggingface.co/jyliuAI/diffusion_baseline/resolve/main/upstreams/flm/scripts/eval_owt_sedd.sh
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hf download hf://jyliuAI/diffusion_baseline/upstreams/flm/scripts/eval_owt_sedd.sh
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curl -L -o eval_owt_sedd.sh https://huggingface.co/jyliuAI/diffusion_baseline/resolve/main/upstreams/flm/scripts/eval_owt_sedd.sh
1.05 kB
| #SBATCH -J eval_sedd # Job name | |
| #SBATCH -o watch_folder/%x_%j.out # log file (out & err) | |
| #SBATCH -N 1 # Total number of nodes requested | |
| #SBATCH --get-user-env # retrieve the users login environment | |
| #SBATCH --mem=100000 # server memory requested (per node) | |
| #SBATCH -t 960:00:00 # Time limit (hh:mm:ss) | |
| #SBATCH --partition=anonymous # Request partition | |
| #SBATCH --constraint="[a5000|a6000|a100|3090]" | |
| #SBATCH --ntasks-per-node=4 | |
| #SBATCH --gres=gpu:4 # Type/number of GPUs needed | |
| #SBATCH --open-mode=append # Do not overwrite logs | |
| #SBATCH --requeue # Requeue upon preemption | |
| checkpoint_path="YOUR_CHECKPOINT_PATH" | |
| export HYDRA_FULL_ERROR=1 | |
| srun python -u -m main \ | |
| mode=ppl_eval \ | |
| loader.batch_size=16 \ | |
| loader.eval_batch_size=16 \ | |
| data=openwebtext-split \ | |
| model=small \ | |
| algo=sedd \ | |
| eval.checkpoint_path=$checkpoint_path \ | |
| sampling.num_sample_batches=0 \ | |
| +wandb.offline=true |