46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
|
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 RaceDataset
|
||
|
|
|
||
|
|
race_reader_cfg = dict(
|
||
|
|
input_columns=['article', 'question', 'A', 'B', 'C', 'D'],
|
||
|
|
output_column='answer')
|
||
|
|
|
||
|
|
race_infer_cfg = dict(
|
||
|
|
prompt_template=dict(
|
||
|
|
type=PromptTemplate,
|
||
|
|
template={
|
||
|
|
ans: dict(
|
||
|
|
round=[
|
||
|
|
dict(role="HUMAN", prompt="Article:\n{article}\nQuestion:\n{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}"),
|
||
|
|
dict(role="BOT", prompt=f'Answer: {ans}'),
|
||
|
|
]
|
||
|
|
)
|
||
|
|
for ans in ['A', 'B', 'C', 'D']
|
||
|
|
}),
|
||
|
|
retriever=dict(type=ZeroRetriever),
|
||
|
|
inferencer=dict(type=PPLInferencer))
|
||
|
|
|
||
|
|
race_eval_cfg = dict(evaluator=dict(type=AccEvaluator))
|
||
|
|
|
||
|
|
race_datasets = [
|
||
|
|
dict(
|
||
|
|
type=RaceDataset,
|
||
|
|
abbr='race-middle',
|
||
|
|
path='race',
|
||
|
|
name='middle',
|
||
|
|
reader_cfg=race_reader_cfg,
|
||
|
|
infer_cfg=race_infer_cfg,
|
||
|
|
eval_cfg=race_eval_cfg),
|
||
|
|
dict(
|
||
|
|
type=RaceDataset,
|
||
|
|
abbr='race-high',
|
||
|
|
path='race',
|
||
|
|
name='high',
|
||
|
|
reader_cfg=race_reader_cfg,
|
||
|
|
infer_cfg=race_infer_cfg,
|
||
|
|
eval_cfg=race_eval_cfg)
|
||
|
|
]
|