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34 lines
1.2 KiB
Python
34 lines
1.2 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 hellaswagDataset_V2
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hellaswag_reader_cfg = dict(
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input_columns=['query', 'A', 'B', 'C', 'D'],
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output_column='label')
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hellaswag_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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ans: dict(round=[
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dict(role="HUMAN", prompt="{ctx}\nQuestion: Which ending makes the most sense?\nA. {A}\nB. {B}\nC. {C}\nD. {D}\nAnswer: "),
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dict(role="BOT", prompt=f"{ans}"),
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]) for ans in ['A', 'B', 'C', 'D']
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}),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=PPLInferencer))
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hellaswag_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
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hellaswag_datasets = [
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dict(
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abbr='hellaswag',
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type=hellaswagDataset_V2,
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path='./data/hellaswag/hellaswag.jsonl',
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reader_cfg=hellaswag_reader_cfg,
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infer_cfg=hellaswag_infer_cfg,
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eval_cfg=hellaswag_eval_cfg)
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]
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