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39 lines
1.1 KiB
Python
39 lines
1.1 KiB
Python
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from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.datasets import NaturalQuestionDataset, NQEvaluator
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nq_reader_cfg = dict(
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input_columns=['question'], output_column='answer', train_split='test')
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nq_infer_cfg = dict(
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ice_template=dict(
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type=PromptTemplate,
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template="Q: </Q>?\nA: </A>",
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column_token_map={
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'question': '</Q>',
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'answer': '</A>'
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}),
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prompt_template=dict(
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type=PromptTemplate,
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template="</E>Question: </Q>? Answer: ",
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column_token_map={
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'question': '</Q>',
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'answer': '</A>'
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},
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ice_token='</E>'),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer))
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nq_eval_cfg = dict(evaluator=dict(type=NQEvaluator))
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nq_datasets = [
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dict(
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type=NaturalQuestionDataset,
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abbr='nq',
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path='/mnt/petrelfs/wuzhiyong/datasets/nq/',
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reader_cfg=nq_reader_cfg,
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infer_cfg=nq_infer_cfg,
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eval_cfg=nq_eval_cfg)
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]
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