datasets = [
    [
        dict(
            abbr='ceval-computer_network',
            eval_cfg=dict(
                evaluator=dict(
                    type='opencompass.openicl.icl_evaluator.AccEvaluator')),
            infer_cfg=dict(
                ice_template=dict(
                    ice_token='</E>',
                    template=dict(
                        A=dict(
                            begin='</E>',
                            round=[
                                dict(
                                    prompt=
                                    '以下是中国关于计算机网络考试的单项选择题，请选出其中的正确答案。\n{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}\n答案: ',
                                    role='HUMAN'),
                                dict(prompt='A', role='BOT'),
                            ]),
                        B=dict(
                            begin='</E>',
                            round=[
                                dict(
                                    prompt=
                                    '以下是中国关于计算机网络考试的单项选择题，请选出其中的正确答案。\n{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}\n答案: ',
                                    role='HUMAN'),
                                dict(prompt='B', role='BOT'),
                            ]),
                        C=dict(
                            begin='</E>',
                            round=[
                                dict(
                                    prompt=
                                    '以下是中国关于计算机网络考试的单项选择题，请选出其中的正确答案。\n{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}\n答案: ',
                                    role='HUMAN'),
                                dict(prompt='C', role='BOT'),
                            ]),
                        D=dict(
                            begin='</E>',
                            round=[
                                dict(
                                    prompt=
                                    '以下是中国关于计算机网络考试的单项选择题，请选出其中的正确答案。\n{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}\n答案: ',
                                    role='HUMAN'),
                                dict(prompt='D', role='BOT'),
                            ])),
                    type=
                    'opencompass.openicl.icl_prompt_template.PromptTemplate'),
                inferencer=dict(
                    type='opencompass.openicl.icl_inferencer.PPLInferencer'),
                retriever=dict(
                    fix_id_list=[
                        0,
                        1,
                        2,
                        3,
                        4,
                    ],
                    type='opencompass.openicl.icl_retriever.FixKRetriever')),
            name='computer_network',
            path='./data/ceval/formal_ceval',
            reader_cfg=dict(
                input_columns=[
                    'question',
                    'A',
                    'B',
                    'C',
                    'D',
                ],
                output_column='answer',
                test_split='val',
                train_split='dev'),
            type='opencompass.datasets.CEvalDataset'),
    ],
]
eval = dict(runner=dict(task=dict()))
models = [
    dict(
        abbr='llama-7b-hf',
        batch_padding=False,
        batch_size=8,
        max_out_len=100,
        max_seq_len=2048,
        model_kwargs=dict(device_map='auto'),
        path='huggyllama/llama-7b',
        run_cfg=dict(num_gpus=1, num_procs=1),
        tokenizer_kwargs=dict(
            padding_side='left', truncation_side='left', use_fast=False),
        tokenizer_path='huggyllama/llama-7b',
        type='opencompass.models.HuggingFaceCausalLM'),
]
work_dir = './outputs/default/20240304_175403'