eval_glm4_9b_chat_vllm.py

from mmengine.config import read_base

with read_base():
    # from ..datasets.ARC_c.ARC_c_gen_1e0de5 import ARC_c_datasets 
    # from ..datasets.ARC_e.ARC_e_gen_1e0de5 import ARC_e_datasets
    from ..datasets.SuperGLUE_BoolQ.SuperGLUE_BoolQ_gen_883d50 import BoolQ_datasets
    from ..summarizers.example import summarizer

datasets = sum([v for k, v in locals().items() if k.endswith("_datasets") or k == 'datasets'], [])
work_dir = './outputs/chatglm4-9b-chat/'

from opencompass.models import VLLMwithChatTemplate

models = [
    dict(
        type=VLLMwithChatTemplate,
        abbr='glm-4-9b-chat-vllm',
        path='THUDM/glm-4-9b-chat',
        max_out_len=1024,
        batch_size=16,
        model_kwargs=dict(tensor_parallel_size=1),
        run_cfg=dict(num_gpus=1),
        stop_words=['<|endoftext|>', '<|user|>', '<|observation|>'],
    )
]