do_sample = False)# obtain from gen_kwargsoutputs=model.generate(input_ids,do_sample=True,temperature=0.95,top_p=0.7,top_k=50,num_beams=1,max_new_tokens=MAX_LENGTH,repetition_penalty=1,length_penalty=1,default_system=None,eos_token_id=tokenizer.eos_token_id,pad_token_id=tokenizer.pad_to...
(chat2,return_tensors="pt").to('cuda')streamer=TextStreamer(tokenizer)stop_token="<|eot_id|>"stop_token_id=tokenizer.encode(stop_token)[0]_=model.generate(**inputs,streamer=streamer,max_new_tokens=512,do_sample=True,temperature=0.1,repetition_penalty=1.2,top_p=0.9,eos_token_id=stop_...
repetition_penalty:一个浮点数,默认为 1.0,指定模型的生成方法中,repetition penalty 的超参数。1.0 意味着没有惩罚。 length_penalty:一个浮点数,默认为 1.0,指定模型的生成方法中,beam-based 方法中针对长度的指数惩罚。它以指数的形式作用在序列长度上,然后把序列的得分除以这个指数结果。 由于序列的得分是对数似...
top_p、top_k、temperature、repetition_penalty:当do_sample=true时,对应的取值将作为服务对应请求参数的默认取值,也可在调用时通过传参进行指定其他值; 超参数默认值:以用户上传generation_config.json配置为准 2 transformers推理框架相关 2.1 推理参数配置 load_model_class:模型加载类,用于加载transformers模型;默认...
'return_dict_in_generate': False, 'forced_bos_token_id': None, 'forced_eos_token_id': None, 'remove_invalid_values': False, 'exponential_decay_length_penalty': None, 'suppress_tokens': None, 'begin_suppress_tokens': None, 'architectures': None, 'finetuning_task': None, 'id2label'...
push_to_hub=False, hub_model_id='baichuan2-7b-chat-lora', hub_private_repo=True, hub_strategy='every_save', hub_token='your-sdk-token', test_oom_error=False, use_flash_attn='auto', max_new_tokens=1024, do_sample=True, temperature=0.9, top_k=20, top_p=0.9, repetition_penalty=...
基于generate的推理 多卡generate推理 基于pipeline的推理 多卡pipeline推理 基于run_mindformer分布式推理 多卡推理 Mindspore-Lite 推理 基本介绍 单卡导出与推理 多卡导出与推理 MindIR 导出 执行推理 模型描述 Code Llama是基于Llama 2的一系列大型代码语言模型,它在开源模型中提供了最先进的性能、填充能力、对...
# model config use_past: True # 开启增量推理 use_moe: False expert_num: 1 per_token_num_experts_chosen: 1 checkpoint_name_or_path: "pangualpha_2_6b" repetition_penalty: 1 max_decode_length: 1024 top_k: 3 top_p: 1 do_sample: False mindspore-lite 如需导出模型,使用mindspor...
repetition_penalty: float, The parameter for repetition penalty. 1.0 means no penalty. add_BOS: bool, Whether add the bos token at the begining of the prompt all_probs: bool # whether return the log prob for all the tokens in vocab compute_logprob: bool # a flag used to compute logpr...
generate sequences that resemble natural ones, i.e., our best results occur in the range ofk > 800 and we specifically chosek = 950 in this work (Fig.1h). As observed with other generative models33,34, our sampling improves when applying a repetition penalty of 1.2. Consequently...