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#!/bin/bash
MODEL_ID="nvidia/Nemotron-4-Mini-Hindi-4B-Instruct"
DATA_FOLDER="ChatRAG-Hi/data"
OUTPUT_FOLDER="ChatRAG-Hi/results"
echo "Running full pipeline for all datasets"
python run_all_evaluation.py \
--mode full \
--model-id "$MODEL_ID" \
--data-folder "$DATA_FOLDER" \
--output-folder "$OUTPUT_FOLDER" \
--all-datasets \
--device cuda \
--num-ctx 5 \
--max-tokens 64 \
--limit 10
echo "Evaluate specific dataset subset"
python run_all_evaluation.py \
--mode full \
--model-id "$MODEL_ID" \
--data-folder "$DATA_FOLDER" \
--output-folder "$OUTPUT_FOLDER" \
--datasets doc2dial quac inscit \
--device cuda
echo "Evaluation only (predictions already exist)"
python run_all_evaluation.py \
--mode evaluation \
--model-id "$MODEL_ID" \
--data-folder "$DATA_FOLDER" \
--output-folder "$OUTPUT_FOLDER" \
--all-datasets
echo "Direct evaluation with get_scores.py"
python get_scores.py \
--results-dir "$OUTPUT_FOLDER" \
--data-path "$DATA_FOLDER" \
--datasets doc2dial quac qrecc inscit hybridial doqa_cooking doqa_travel doqa_movies convfinqa \
--output-csv "${OUTPUT_FOLDER}/scores.csv" |