#!/bin/bash

MODEL_PATH="cognitivecomputations/dolphin-2.8-mistral-7b-v02"
MODEL_NAME="dolphin-2.8-mistral-7b-v02"
RESULTS_PATH="/workspace/results/$MODEL_NAME"
mkdir -p "$RESULTS_PATH"

MODEL_ARGS="pretrained=$MODEL_PATH,dtype=auto"

tasks=(
    "truthfulqa" 
    "winogrande"
    "gsm8k" 
    "hellaswag" 
    "arc_challenge" 
    "mmlu" 
    )

# Function to get the number of fewshot for a given task
get_num_fewshot() {
    case "$1" in
        "mmlu")          echo 5 ;;
        "truthfulqa")    echo 0 ;;
        "gsm8k")         echo 5 ;;
        "hellaswag")     echo 10 ;;
        "arc_challenge") echo 25 ;;
        "winogrande")    echo 5 ;;
        *)               echo 0 ;;
    esac
}

for TASK in "${tasks[@]}"; do
    lm_eval --model hf --model_args "$MODEL_ARGS" --task="$TASK" --num_fewshot "$(get_num_fewshot "$TASK")" --device cuda:0 --batch_size 8 --output_path "$RESULTS_PATH/$TASK.json"
    # lm_eval --model vllm --model_args "$MODEL_ARGS" --task="$TASK" --num_fewshot "$(get_num_fewshot "$TASK")" --batch_size 8 --output_path "$RESULTS_PATH/$TASK.json"

done


jq -s '[.[]]' $RESULTS_PATH/*.json > $RESULTS_PATH/eval_results.json

huggingface-cli upload cognitivecomputations/$MODEL_NAME $RESULTS_PATH/eval_results.json
huggingface-cli upload cognitivecomputations/$MODEL_NAME eval.sh

# docker run -it --network=host --group-add=video --ipc=host --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --device /dev/kfd --device /dev/dri -v /workspace/models/dolphin-phi-kensho:/app/model embeddedllminfo/vllm-rocm bash