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datasets = [
[
dict(
abbr='siqa',
eval_cfg=dict(
evaluator=dict(
type='opencompass.openicl.icl_evaluator.EDAccEvaluator'),
pred_role='BOT'),
infer_cfg=dict(
inferencer=dict(
type='opencompass.openicl.icl_inferencer.GenInferencer'),
prompt_template=dict(
template=dict(round=[
dict(
prompt=
'{context}\nQuestion: {question}\nA. {answerA}\nB. {answerB}\nC. {answerC}\nAnswer:',
role='HUMAN'),
]),
type=
'opencompass.openicl.icl_prompt_template.PromptTemplate'),
retriever=dict(
type='opencompass.openicl.icl_retriever.ZeroRetriever')),
path='./data/siqa',
reader_cfg=dict(
input_columns=[
'context',
'question',
'answerA',
'answerB',
'answerC',
],
output_column='all_labels',
test_split='validation'),
type='opencompass.datasets.siqaDataset_V2'),
],
]
eval = dict(runner=dict(task=dict()))
models = [
dict(
abbr='my_api',
batch_size=8,
key='',
max_out_len=100,
max_seq_len=2048,
meta_template=dict(round=[
dict(begin='<reserved_106>', role='HUMAN'),
dict(begin='<reserved_107>', generate=True, role='BOT'),
]),
model_kwargs=dict(device_map='auto', trust_remote_code=True),
path='http://127.0.0.1:12345/testing',
run_cfg=dict(num_gpus=1, num_procs=1),
type='opencompass.models.my_api.MyAPIModel'),
]
work_dir = './outputs/default/20240306_161832'
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