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from mmengine.config import read_base
from opencompass.models.turbomind_tis import TurboMindTisModel
with read_base():
# choose a list of datasets
from .datasets.mmlu.mmlu_gen_a484b3 import mmlu_datasets
from .datasets.ceval.ceval_gen_5f30c7 import ceval_datasets
from .datasets.SuperGLUE_WiC.SuperGLUE_WiC_gen_d06864 import WiC_datasets
from .datasets.triviaqa.triviaqa_gen_2121ce import triviaqa_datasets
from .datasets.gsm8k.gsm8k_gen_1d7fe4 import gsm8k_datasets
from .datasets.humaneval.humaneval_gen_8e312c import humaneval_datasets
# and output the results in a choosen format
from .summarizers.medium import summarizer
datasets = sum((v for k, v in locals().items() if k.endswith('_datasets')), [])
models = [
dict(
type=TurboMindTisModel,
abbr='internlm-chat-20b-turbomind',
path="internlm",
tis_addr='0.0.0.0:33337',
max_out_len=100,
max_seq_len=2048,
batch_size=8,
run_cfg=dict(num_gpus=1, num_procs=1),
)
]
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