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run_inference_only_eeg.sh
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37 lines (32 loc) · 1.39 KB
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#!/bin/bash
# Declare array for LLM models
#llms=("mistralai/Mistral-7B-Instruct-v0.3" "meta-llama/Meta-Llama-3-8B-Instruct" "Qwen/Qwen2.5-7B-Instruct")
#llms=("$1")
mkdir -p results
# Loop over each LLM model
for llm in "${llms[@]}"; do
# Extract the second half of the LLM model for the output directory
llm_name=$(echo "$llm" | awk -F '/' '{print $2}')
# Construct the output directory name
model_path="all_models/${llm_name}_all"
model_path1="all_models/${llm_name}_no_stage2_all"
# Run the Python command
results_csv="results/results_${llm_name}_only_eeg.csv"
results_csv1="results/results_${llm_name}_no_stage2_only_eeg.csv"
# Execute the python inference command
python inference_only_eeg.py --model_path "$model_path" \
--eeg_dataset data/block/eeg_55_95_std.pth \
--image_dir data/images/ \
--dest "$results_csv" \
--splits_path data/block/block_splits_by_image_all.pth
python inference_only_eeg.py --model_path "$model_path1" \
--eeg_dataset data/block/eeg_55_95_std.pth \
--image_dir data/images/ \
--dest "$results_csv1" \
--splits_path data/block/block_splits_by_image_all.pth
# Check if the command executed successfully
if [ $? -ne 0 ]; then
echo "Error with LLM $llm"
exit 1
fi
done