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='baichuan2-7b-chat-hf', batch_size=8, max_out_len=100, max_seq_len=2048, meta_template=dict(round=[ dict(begin='', role='HUMAN'), dict(begin='', generate=True, role='BOT'), ]), model_kwargs=dict(device_map='auto', trust_remote_code=True), path='/export/home/tanwentao1/data/Baichuan2-7B-Chat/', run_cfg=dict(num_gpus=1, num_procs=1), tokenizer_kwargs=dict( padding_side='left', truncation_side='left', trust_remote_code=True, use_fast=False), tokenizer_path='/export/home/tanwentao1/data/Baichuan2-7B-Chat/', type='opencompass.models.HuggingFaceCausalLM'), ] work_dir = './outputs/default/20240306_170630'