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b564e608b1
* Add MedXpertQA * Add MedXpertQA * Add MedXpertQA * Fix lint --------- Co-authored-by: MaiziXiao <xxllcc1993@gmail.com>
58 lines
1.5 KiB
Python
58 lines
1.5 KiB
Python
from opencompass.datasets import MedXpertQADataset, MedXpertQAEvaluator
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from opencompass.openicl.icl_inferencer import GenInferencer
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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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SYSTEM_PROMPT = 'You are a helpful medical assistant.\n\n' # Where to put this?
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ZERO_SHOT_PROMPT = 'Q: {question}\nA: Among {start} through {end}, the answer is'
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# Reader configuration
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reader_cfg = dict(
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input_columns=[
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'question',
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'options',
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'medical_task',
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'body_system',
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'question_type',
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'prompt_mode',
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],
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output_column='label',
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)
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# Inference configuration
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infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(
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begin=[
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dict(role='SYSTEM', fallback_role='HUMAN', prompt=SYSTEM_PROMPT),
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],
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round=[
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dict(
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role='HUMAN',
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prompt=ZERO_SHOT_PROMPT, # prompt mode: zero-shot
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),
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],
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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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)
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# Evaluation configuration
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eval_cfg = dict(
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evaluator=dict(type=MedXpertQAEvaluator),
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pred_role='BOT',
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)
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medxpertqa_dataset = dict(
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type=MedXpertQADataset,
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abbr='medxpertqa',
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path='TsinghuaC3I/MedXpertQA',
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prompt_mode='zero-shot',
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reader_cfg=reader_cfg,
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infer_cfg=infer_cfg,
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eval_cfg=eval_cfg,
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)
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medxpertqa_datasets = [medxpertqa_dataset]
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