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from opencompass.multimodal.models.qwen import QwenVLMMBenchPromptConstructor
# dataloader settings
val_pipeline = [
dict(type='mmpretrain.torchvision/Resize',
size=(448, 448),
interpolation=3),
dict(type='mmpretrain.torchvision/ToTensor'),
dict(type='mmpretrain.torchvision/Normalize',
mean=(0.48145466, 0.4578275, 0.40821073),
std=(0.26862954, 0.26130258, 0.27577711)),
dict(type='mmpretrain.PackInputs',
algorithm_keys=[
'question', 'options', 'category', 'l2-category', 'context',
'index', 'options_dict'
])
]
dataset = dict(type='opencompass.MMBenchDataset',
data_file='/mnt/petrelfs/share_data/yuanyike/cnbench_v010_rolling.tsv',
pipeline=val_pipeline,
sys_prompt='请从以下选项中选择一个正确选项。')
qwen_mmbench_dataloader = dict(batch_size=1,
num_workers=4,
dataset=dataset,
collate_fn=dict(type='pseudo_collate'),
sampler=dict(type='DefaultSampler', shuffle=False))
# model settings
qwen_model = dict(
type='qwen-vl-chat',
pretrained_path='Qwen/Qwen-VL-Chat', # or Huggingface repo id
prompt_constructor=dict(type=QwenVLMMBenchPromptConstructor)
)
# evaluation settings
qwen_mmbench_evaluator = [
dict(type='opencompass.DumpResults',
save_path='work_dirs/qwenvl-chat-7b-cnbench-v010.xlsx')
]
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