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39 lines
1.3 KiB
Python
39 lines
1.3 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 QuALITYDataset, QuALITYEvaluator
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from opencompass.utils.text_postprocessors import first_option_postprocess
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QuALITY_reader_cfg = dict(
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input_columns=['article', 'question', 'A', 'B', 'C', 'D'],
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output_column='gold_label',
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)
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QuALITY_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(round=[
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dict(
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role="HUMAN",
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prompt=
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"Read the article, and answer the question.\n\nArticle:\n{article}\n\nQ: {question}\n\nA. {A}\nB. {B}\nC. {C}\nD. {D}"
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),
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])),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer))
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QuALITY_eval_cfg = dict(
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evaluator=dict(type=QuALITYEvaluator),
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pred_postprocessor=dict(type=first_option_postprocess, options='ABCD'),
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pred_role='BOT')
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QuALITY_datasets = [
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dict(
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abbr='QuALITY',
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type=QuALITYDataset,
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path='./data/QuALITY/QuALITY.v1.0.1.htmlstripped.dev',
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reader_cfg=QuALITY_reader_cfg,
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infer_cfg=QuALITY_infer_cfg,
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eval_cfg=QuALITY_eval_cfg),
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]
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