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from mmengine.config import read_base |
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from opencompass.models.xunfei_api import XunFei |
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from opencompass.partitioners import NaivePartitioner |
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from opencompass.runners.local_api import LocalAPIRunner |
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from opencompass.tasks import OpenICLInferTask |
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with read_base(): |
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from ..summarizers.medium import summarizer |
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from ..datasets.ceval.ceval_gen import ceval_datasets |
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datasets = [ |
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*ceval_datasets, |
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] |
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models = [ |
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dict( |
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abbr='Spark-v1-1', |
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type=XunFei, |
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appid="xxxx", |
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path='ws://spark-api.xf-yun.com/v1.1/chat', |
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api_secret = "xxxxxxx", |
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api_key = "xxxxxxx", |
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query_per_second=1, |
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max_out_len=2048, |
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max_seq_len=2048, |
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batch_size=8), |
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dict( |
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abbr='Spark-v3-1', |
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type=XunFei, |
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appid="xxxx", |
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domain='generalv3', |
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path='ws://spark-api.xf-yun.com/v3.1/chat', |
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api_secret = "xxxxxxxx", |
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api_key = "xxxxxxxxx", |
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query_per_second=1, |
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max_out_len=2048, |
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max_seq_len=2048, |
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batch_size=8), |
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] |
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infer = dict( |
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partitioner=dict(type=NaivePartitioner), |
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runner=dict( |
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type=LocalAPIRunner, |
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max_num_workers=2, |
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concurrent_users=2, |
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task=dict(type=OpenICLInferTask)), |
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) |
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work_dir = "outputs/api_xunfei/" |
