OpenCompass/opencompass/configs/datasets/nq/nq_xfinder_gen_3dcea1.py
liushz 00fc8da5be
[Feature] Add model postprocess function (#1484)
* Add model postprocess function

* Add model postprocess function

* Add model postprocess function

* Add model postprocess function

* Add model postprocess function

* Add model postprocess function

* Add model postprocess function

* Add model postprocess function

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Co-authored-by: liushz <liuhongwei@pjlab.rog.cn>
2024-09-05 21:10:29 +08:00

38 lines
1.2 KiB
Python

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.datasets import NaturalQuestionDataset, NQEvaluator
from opencompass.utils.model_postprocessors import xfinder_postprocess
nq_reader_cfg = dict(
input_columns=['question'], output_column='answer', train_split='test')
nq_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template=dict(
round=[
dict(role='HUMAN', prompt='Question: {question}?\nAnswer: '),
], )),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=GenInferencer))
nq_eval_cfg = dict(
evaluator=dict(type=NQEvaluator), pred_role='BOT',
model_postprocessor=dict(
type=xfinder_postprocess,
question_type='short_text',
xfinder_model_name='xFinder-qwen1505',
xfiner_api_url='http://0.0.0.0:23333/v1,http://0.0.0.0:23334/v1')
)
nq_datasets = [
dict(
type=NaturalQuestionDataset,
abbr='nq',
path='opencompass/natural_question',
reader_cfg=nq_reader_cfg,
infer_cfg=nq_infer_cfg,
eval_cfg=nq_eval_cfg)
]