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lunch.slurm
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lunch.slurm
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#!/bin/bash
#SBATCH --job-name=compute-information # create a short name for your job
#SBATCH --output="compute-information-%j.out"
#SBATCH --partition=gpu
#SBATCH --qos=gpu085862023
#SBATCH --gres=gpu
source venv/bin/activate
module load cuda
#for at in 10 100 1000 10000
#do
# python benchmark_sparse_retrieval_from_pyterrier_bow.py beir_datasets/msmarco $at
# python benchmark_sparse_retrieval_from_pyterrier_bow.py beir_datasets/msmarco $at --algorithm iterative --objective half --fp_16
#python benchmark_sparse_retrieval_from_splade.py beir_datasets/msmarco 1000
#python benchmark_sparse_retrieval_from_splade.py beir_datasets/msmarco 1000 --algorithm iterative --objective half
#done
python compute_information.py clean_datasets/math__openai_grade_school_clean.jsonl EleutherAI/gpt-neo-125m --context-percentage 0.25 --dtype float32
python compute_information.py clean_datasets/math__openai_grade_school_clean.jsonl EleutherAI/gpt-neo-125m --context-percentage 0.25 --dtype float16
python compute_information.py clean_datasets/math__openai_grade_school_clean.jsonl EleutherAI/gpt-neo-125m --context-percentage 0.25 --dtype bfloat16
python compute_information.py clean_datasets/math__openai_grade_school_clean.jsonl EleutherAI/gpt-neo-125m --context-percentage 0.25 --dtype int8
python compute_information.py clean_datasets/math__openai_grade_school_clean.jsonl EleutherAI/gpt-neo-125m --context-percentage 0.25 --dtype int4
deactivate