| set -e | |
| set -x | |
| PROJECT_ROOT="<PATH_TO_YOUR_PROJECT_ROOT>" | |
| MODEL_PATH="<PATH_TO_YOUR_LLADA2_MINI_WEIGHTS>" | |
| BASE_OUTPUT_PATH="${PROJECT_ROOT}/outputs/baseline_math500" | |
| cd "$PROJECT_ROOT" | |
| export CUDA_VISIBLE_DEVICES=0 | |
| export HF_ENDPOINT=https://hf-mirror.com | |
| LENGTH=256 | |
| STEPS=32 | |
| BLOCK=32 | |
| TASK="math500" | |
| TYPE="math" | |
| NAME="baseline_n1" | |
| mkdir -p "${BASE_OUTPUT_PATH}/${NAME}" | |
| accelerate launch evaluation_script.py \ | |
| --model LLaDA2 \ | |
| --tasks ${TASK} \ | |
| --batch_size 1 \ | |
| --model_args "pretrained=${MODEL_PATH},assistant_prefix=<reasoning> " \ | |
| --gen_kwargs "use_hts=True,hts_N=1,hts_mode=False,steps=${STEPS},block_length=${BLOCK},gen_length=${LENGTH},task_type=${TYPE},temperature=0.7,realtime_output=${BASE_OUTPUT_PATH}/${NAME}/baseline.jsonl" \ | |
| --num_fewshot 0 \ | |
| --output_path "${BASE_OUTPUT_PATH}/${NAME}" |