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# vllm serve meta-llama/Llama-3.3-70B-Instruct --port 8004 --tensor-parallel-size 4 --max-model-len 16384 --gpu-memory-utilization 0.9
BATCH_SIZE=100
# BATCH_SIZE=20
# Loop over eval sizes and datasets
for EVAL_SIZE in 20; do
for DATASET in math-500; do
# Convert dataset name for file paths (replace - with _)
DATASET_FILE=$(echo ${DATASET} | tr '-' '_')
echo "Running experiments for dataset: ${DATASET} with eval_size ${EVAL_SIZE}"
# debug experiment
python3 run.py --experiment_type debug --dataset ${DATASET} --eval_size ${EVAL_SIZE} --max_turns 10 --batch_size ${BATCH_SIZE} \
--user_model_name hosted_vllm/meta-llama/Llama-3.3-70B-Instruct --user_api_base http://localhost:8004/v1 --user_api_key EMPTY \
--collaborator_model_name hosted_vllm/meta-llama/Llama-3.3-70B-Instruct --collaborator_api_base http://localhost:8004/v1 --collaborator_api_key EMPTY \
--judge_model_name hosted_vllm/meta-llama/Llama-3.3-70B-Instruct --judge_api_base http://localhost:8004/v1 --judge_api_key EMPTY \
--output_file /shared/storage-01/users/mehri2/mem/collaborativeagents/scripts/runs/llama70b/debug/${DATASET_FILE}_llama70b_user_llama70b_agent_debug_eval_size_${EVAL_SIZE}.jsonl \
>> ./runs/llama70b/debug/${DATASET_FILE}_llama70b_user_llama70b_agent_debug_eval_size_${EVAL_SIZE}.out 2>&1
done
done
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