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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
1.6 KiB
Python
52 lines
1.6 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import FixKRetriever
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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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_hint = 'The following are semantic matching questions. \n' \
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'Please determine whether the following two sentences are semantically duplicate: ' \
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'0 means not duplicate, 1 means duplicate.\n'
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QQP_infer_cfg = dict(
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ice_template=dict(
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type=PromptTemplate,
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template='Sentence one: {question1}\nSentence two: {question2}\nResult: {label}',
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),
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prompt_template=dict(
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type=PromptTemplate,
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template={
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answer:
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f'{_hint}</E>Sentence one: {{question1}}\nSentence two: {{question2}}\nResult: {answer}'
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for answer in [0, 1]
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},
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ice_token='</E>',
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),
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retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4]),
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inferencer=dict(type=PPLInferencer))
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QQP_eval_cfg = dict(evaluator=dict(type=AccEvaluator), )
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QQP_datasets = []
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for _split in ['validation', 'test']:
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QQP_reader_cfg = dict(
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input_columns=['question1', 'question2'],
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output_column='label',
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train_split='train',
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test_split=_split
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)
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QQP_datasets.append(
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dict(
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abbr=f'QQP-{_split}',
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type=HFDataset,
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path='glue',
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name='qqp',
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reader_cfg=QQP_reader_cfg,
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infer_cfg=QQP_infer_cfg,
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eval_cfg=QQP_eval_cfg
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)
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)
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