opencompass / tmp /0bd141af-ea86-420f-b26c-b2890fc57de2_params.py
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datasets = [
[
dict(
abbr='LongBench_trec',
eval_cfg=dict(
evaluator=dict(
type='opencompass.datasets.LongBenchClassificationEvaluator'
),
pred_postprocessor=dict(
type='opencompass.datasets.trec_postprocess'),
pred_role='BOT'),
infer_cfg=dict(
inferencer=dict(
max_out_len=64,
type='opencompass.openicl.icl_inferencer.GenInferencer'),
prompt_template=dict(
template=dict(round=[
dict(
prompt=
'Please determine the type of the question below. Here are some examples of questions.\n\n{context}\n{input}',
role='HUMAN'),
]),
type=
'opencompass.openicl.icl_prompt_template.PromptTemplate'),
retriever=dict(
type='opencompass.openicl.icl_retriever.ZeroRetriever')),
name='trec',
path='opencompass/Longbench',
reader_cfg=dict(
input_columns=[
'context',
'input',
],
output_column='all_labels',
test_split='test',
train_split='test'),
type='opencompass.datasets.LongBenchtrecDataset'),
],
]
eval = dict(runner=dict(task=dict(dump_details=True)))
models = [
dict(
abbr='gated_deltanet',
batch_size=128,
max_seq_len=2048,
model_kwargs=dict(
device_map='auto',
torch_dtype='torch.bfloat16',
trust_remote_code=True),
path='download_model/hgrn2-1.3B-100B',
run_cfg=dict(num_gpus=1),
tokenizer_kwargs=dict(padding_side='left', truncation_side='left'),
tokenizer_path='download_model/hgrn2-1.3B-100B',
type='opencompass.models.HuggingFaceBaseModel'),
]
work_dir = 'outputs/default/20251219_164057'