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* [Feature] Support import configs/models/summarizers from whl * Update LCBench configs * Update * Update * Update * Update * update * Update * Update * Update * Update * Update
52 lines
1.4 KiB
Python
52 lines
1.4 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 GenInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets import SummeditsDataset_V2
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from opencompass.utils.text_postprocessors import first_capital_postprocess
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summedits_reader_cfg = dict(
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input_columns=['doc', 'summary'], output_column='label')
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summedits_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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"""Given the document below, you have to determine if "Yes" or "No", the summary is factually consistent with the document.
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Document:
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{doc}
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Summary:
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{summary}
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Question:
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Is the summary factually consistent with the document?
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A. Yes
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B. No
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Answer:"""
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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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summedits_eval_cfg = dict(
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evaluator=dict(type=AccEvaluator),
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pred_role='BOT',
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pred_postprocessor=dict(type=first_capital_postprocess),
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)
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summedits_datasets = [
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dict(
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abbr='summedits',
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type=SummeditsDataset_V2,
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path='opencompass/summedits',
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reader_cfg=summedits_reader_cfg,
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infer_cfg=summedits_infer_cfg,
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eval_cfg=summedits_eval_cfg)
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]
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