datasets = [
    [
        dict(
            abbr='LongBench_lsht',
            eval_cfg=dict(
                evaluator=dict(
                    type='opencompass.datasets.LongBenchClassificationEvaluator'
                ),
                pred_postprocessor=dict(
                    type='opencompass.datasets.lsht_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='请判断给定新闻的类别，下面是一些例子。\n\n{context}\n{input}',
                            role='HUMAN'),
                    ]),
                    type=
                    'opencompass.openicl.icl_prompt_template.PromptTemplate'),
                retriever=dict(
                    type='opencompass.openicl.icl_retriever.ZeroRetriever')),
            name='lsht',
            path='opencompass/Longbench',
            reader_cfg=dict(
                input_columns=[
                    'context',
                    'input',
                ],
                output_column='all_labels',
                test_split='test',
                train_split='test'),
            type='opencompass.datasets.LongBenchlshtDataset'),
    ],
]
eval = dict(runner=dict(task=dict(dump_details=True)))
models = [
    dict(
        abbr='retnet',
        batch_size=128,
        max_seq_len=2048,
        model_kwargs=dict(
            device_map='auto',
            torch_dtype='torch.bfloat16',
            trust_remote_code=True),
        path='/mnt/jfzn/msj/retnet-1.3B-100B',
        run_cfg=dict(num_gpus=1),
        tokenizer_kwargs=dict(padding_side='left', truncation_side='left'),
        tokenizer_path='/mnt/jfzn/msj/retnet-1.3B-100B',
        type='opencompass.models.HuggingFaceBaseModel'),
]
work_dir = 'outputs/default/20251207_222645'