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55 lines
1.8 KiB
Python
55 lines
1.8 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 cmnliDataset
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cmnli_reader_cfg = dict(
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input_columns=['sentence1', 'sentence2'],
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output_column='label',
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test_split='train')
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cmnli_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="语句一：“{sentence1}”\n语句二：“{sentence2}”\n请问这两句话是什么关系？"
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),
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dict(role="BOT", prompt="矛盾")
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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="语句一：“{sentence1}”\n语句二：“{sentence2}”\n请问这两句话是什么关系？"
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),
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dict(role="BOT", prompt="蕴含")
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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",
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prompt="语句一：“{sentence1}”\n语句二：“{sentence2}”\n请问这两句话是什么关系？"
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),
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dict(role="BOT", prompt="无关")
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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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cmnli_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
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cmnli_datasets = [
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dict(
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abbr="cmnli",
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type=cmnliDataset,
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path='./data/CLUE/cmnli/cmnli_public/dev.json',
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reader_cfg=cmnli_reader_cfg,
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infer_cfg=cmnli_infer_cfg,
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eval_cfg=cmnli_eval_cfg)
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]
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