BLEUBERI/eval/WildBench/scripts/gemma-2-27b-it@together.sh
2025-06-04 20:36:43 +00:00

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# export ANTHROPIC_API_KEY=your_anthropic_api_key
model_name="google/gemma-2-27b-it@together"
model_pretty_name="gemma-2-27b-it@together"
output_dir="result_dirs/wild_bench_v2/"
TEMP=0; TOP_P=1.0; MAX_TOKENS=4096;
# shard_size should be 1024 // n_shards
n_shards=8
shard_size=128
start_gpu=0
shards_dir="${output_dir}/tmp_${model_pretty_name}"
for ((start = 0, end = (($shard_size)), gpu = $start_gpu; gpu < $n_shards+$start_gpu; start += $shard_size, end += $shard_size, gpu++)); do
python src/unified_infer.py \
--data_name wild_bench \
--start_index $start --end_index $end \
--engine together \
--model_name $model_name \
--top_p $TOP_P --temperature $TEMP \
--max_tokens $MAX_TOKENS \
--output_folder $shards_dir &
done
wait
python src/merge_results.py $shards_dir/ $model_pretty_name
cp $shards_dir/${model_pretty_name}.json $output_dir/${model_pretty_name}.json