OpenCompass/opencompass/configs/datasets/subjective/wildbench/wildbench_single_judge.py
Songyang Zhang 46cc7894e1
[Feature] Support import configs/models/summarizers from whl (#1376)
* [Feature] Support import configs/models/summarizers from whl

* Update LCBench configs

* Update

* Update

* Update

* Update

* update

* Update

* Update

* Update

* Update

* Update
2024-08-01 00:42:48 +08:00

48 lines
1.3 KiB
Python

from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import ChatInferencer, GenInferencer
from opencompass.openicl.icl_evaluator import LMEvaluator
from opencompass.datasets import WildBenchDataset
subjective_reader_cfg = dict(
input_columns=['dialogue', 'prompt'],
output_column='judge',
)
data_path ='./data/WildBench/wildbench.jsonl'
wildbench_single_datasets = []
# the question is a list, how to process it
subjective_infer_cfg = dict(
prompt_template=dict(
type=PromptTemplate,
template="""{dialogue}"""
),
retriever=dict(type=ZeroRetriever),
inferencer=dict(type=ChatInferencer, max_seq_len=4096, max_out_len=512, infer_mode='last'),
)
subjective_eval_cfg = dict(
evaluator=dict(
type=LMEvaluator,
prompt_template=dict(
type=PromptTemplate,
template="""{prompt}"""
),
),
pred_role='BOT',
)
wildbench_single_datasets.append(
dict(
abbr='wildbench',
type=WildBenchDataset,
path=data_path,
eval_mode='single',
reader_cfg=subjective_reader_cfg,
infer_cfg=subjective_infer_cfg,
eval_cfg=subjective_eval_cfg
))