from opencompass.openicl.icl_prompt_template import PromptTemplate from opencompass.openicl.icl_retriever import ZeroRetriever from opencompass.openicl.icl_inferencer import PPLInferencer from opencompass.openicl.icl_evaluator import AccEvaluator from opencompass.datasets import WSCDataset WSC_reader_cfg = dict( input_columns=['span1', 'span2', 'text', 'new_text'], output_column='answer', ) WSC_infer_cfg = dict( prompt_template=dict( type=PromptTemplate, template={ 0: dict(round=[ dict(role='HUMAN', prompt='{text}'), ]), 1: dict(round=[ dict(role='HUMAN', prompt='{new_text}'), ]), }, ), retriever=dict(type=ZeroRetriever), inferencer=dict(type=PPLInferencer), ) WSC_eval_cfg = dict(evaluator=dict(type=AccEvaluator)) WSC_datasets = [ dict( type=WSCDataset, path='json', abbr='WSC', data_files='./data/SuperGLUE/WSC/val.jsonl', split='train', reader_cfg=WSC_reader_cfg, infer_cfg=WSC_infer_cfg, eval_cfg=WSC_eval_cfg, ) ]