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52 lines
1.7 KiB
Python
52 lines
1.7 KiB
Python
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 PPLInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import HFDataset
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ocnli_reader_cfg = dict(
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input_columns=['sentence1', 'sentence2'], output_column='label')
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# TODO: two prompt templates for ocnli
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ocnli_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template={
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'contradiction':
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dict(round=[
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dict(
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role="HUMAN",
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prompt="阅读文章：{sentence1}\n根据上文，回答如下问题：{sentence2}？"),
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dict(role="BOT", prompt="错")
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]),
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'entailment':
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dict(round=[
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dict(
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role="HUMAN",
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prompt="阅读文章：{sentence1}\n根据上文，回答如下问题：{sentence2}？"),
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dict(role="BOT", prompt="对")
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]),
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'neutral':
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dict(round=[
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dict(
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role="HUMAN", prompt="如果{sentence1}为真，那么{sentence2}也为真吗？"),
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dict(role="BOT", prompt="可能")
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]),
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}),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=PPLInferencer))
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ocnli_eval_cfg = dict(evaluator=dict(type=AccEvaluator), )
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ocnli_datasets = [
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dict(
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type=HFDataset,
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abbr='ocnli',
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path='json',
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split='train',
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data_files='./data/CLUE/OCNLI/dev.json',
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reader_cfg=ocnli_reader_cfg,
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infer_cfg=ocnli_infer_cfg,
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eval_cfg=ocnli_eval_cfg)
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]
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