datasets = [ [ dict( abbr='LongBench_2wikimqa', eval_cfg=dict( evaluator=dict( type='opencompass.datasets.LongBenchF1Evaluator'), pred_role='BOT'), infer_cfg=dict( inferencer=dict( max_out_len=32, type='opencompass.openicl.icl_inferencer.GenInferencer'), prompt_template=dict( template=dict(round=[ dict( prompt= 'Answer the question based on the given passages. Only give me the answer and do not output any other words.\n\nThe following are given passages.\n{context}\n\nAnswer the question based on the given passages. Only give me the answer and do not output any other words.\n\nQuestion: {input}\nAnswer:', role='HUMAN'), ]), type= 'opencompass.openicl.icl_prompt_template.PromptTemplate'), retriever=dict( type='opencompass.openicl.icl_retriever.ZeroRetriever')), name='2wikimqa', path='opencompass/Longbench', reader_cfg=dict( input_columns=[ 'context', 'input', ], output_column='answers', test_split='test', train_split='test'), type='opencompass.datasets.LongBench2wikimqaDataset'), ], ] 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_163447'