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66 lines
2.1 KiB
Python
66 lines
2.1 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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bustm_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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bustm_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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0:
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dict(
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begin=[
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dict(
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role='SYSTEM',
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fallback_role='HUMAN',
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prompt="请判断以下两句话说的是否是一个意思：")
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],
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round=[
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dict(role="HUMAN", prompt="{sentence1}，{sentence2}"),
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dict(role="BOT", prompt="两句话说的毫不相关。")
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]),
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1:
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dict(
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begin=[
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dict(
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role='SYSTEM',
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fallback_role='HUMAN',
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prompt="请判断以下两句话说的是否是一个意思：")
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],
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round=[
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dict(role="HUMAN", prompt="{sentence1}，{sentence2}"),
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dict(role="BOT", prompt="两句话说是的一个意思。")
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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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bustm_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
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bustm_datasets = [
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dict(
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type=HFDataset,
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abbr='bustm-dev',
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path='json',
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data_files='./data/FewCLUE/bustm/dev_few_all.json',
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split='train',
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reader_cfg=bustm_reader_cfg,
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infer_cfg=bustm_infer_cfg,
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eval_cfg=bustm_eval_cfg),
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dict(
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type=HFDataset,
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abbr='bustm-test',
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path='json',
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data_files='./data/FewCLUE/bustm/test_public.json',
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split='train',
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reader_cfg=bustm_reader_cfg,
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infer_cfg=bustm_infer_cfg,
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eval_cfg=bustm_eval_cfg)
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]
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