2023-07-05 10:22:40 +08:00
|
|
|
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 C3Dataset
|
|
|
|
|
|
|
|
C3_reader_cfg = dict(
|
|
|
|
input_columns=[
|
|
|
|
'question', 'content', 'choice0', 'choice1', 'choice2', 'choice3',
|
|
|
|
'choices'
|
|
|
|
],
|
|
|
|
output_column='label')
|
|
|
|
|
|
|
|
C3_infer_cfg = dict(
|
|
|
|
prompt_template=dict(
|
|
|
|
type=PromptTemplate,
|
|
|
|
template={
|
|
|
|
i: dict(round=[
|
2024-05-14 15:35:58 +08:00
|
|
|
dict(role='HUMAN', prompt='文章:{content}\n问题:{question}'),
|
|
|
|
dict(role='BOT', prompt=f'答案:{{choice{i}}}')
|
2023-07-05 10:22:40 +08:00
|
|
|
])
|
|
|
|
for i in range(4)
|
|
|
|
}),
|
|
|
|
retriever=dict(type=ZeroRetriever),
|
|
|
|
inferencer=dict(type=PPLInferencer))
|
|
|
|
|
|
|
|
C3_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
|
|
|
|
|
|
|
|
C3_datasets = [
|
|
|
|
dict(
|
|
|
|
type=C3Dataset,
|
|
|
|
abbr='C3',
|
|
|
|
path='./data/CLUE/C3/dev_0.json',
|
|
|
|
reader_cfg=C3_reader_cfg,
|
|
|
|
infer_cfg=C3_infer_cfg,
|
|
|
|
eval_cfg=C3_eval_cfg)
|
|
|
|
]
|