max_length(int, optional, defaults to model.config.max_length) — The maximum length of the sequence to be generated. max_length:生成序列的最大长度。 min_length(int, optional, defaults to 10) — The minimum length of the sequence to be generated. min_length:生成序列的最短长度,默认是10。
max_new_tokens=3, ) # 直接指定使用其函数 # generation_output = model.greedy_search( # input_ids=input_ids, # num_beams = 1, # do_sample = False, # return_dict_in_generate=True, # max_length = 7 # ) print("query:", text) for i, output_sequence in enumerate(generation...
model.generate(input_text, max_length=50) ``` 3. temperature temperature参数用于控制生成文本的多样性,通过调整该参数可以控制生成文本的随机程度。较大的temperature值将增加生成文本的多样性。若需要生成的文本更富有变化,可以将temperature设置为较大的值。 ```python model.generate(input_text, temperature=1.5...
input_text = "Once upon a time," generated_text = model.generate(tokenizer.encode(input_text, return_tensors="pt"), max_length=50, num_beams=5)[0] print(tokenizer.decode(generated_text, skip_special_tokens=True)) 2. chat 方法 chat方法是一个高级的便捷方法,通常用于模拟对话。 提供了更简...
使用时需要传递一些参数,如max_length(生成文本的最大长度)、num_beams(束搜索的数量,用于增强生成的多样性)等。 from transformers import GPT2LMHeadModel, GPT2Tokenizer model_name ="gpt2"model = GPT2LMHeadModel.from_pretrained(model_name)
In pytorch, even if the max_length argument is smaller than the length of the input sequence, a token is still generated. The following example using GPT2 is quite clear. The source of the bug is from generation_utils which only throws a warning in pytorch while throwing an error in ...
现在让我们尝试一些更有趣的东西:我们能重现OpenAI的独角兽故事吗?正如我们之前所做的,我们将用标记器对提示进行编码,并且我们将为max_length指定一个较大的值,以生成一个较长的文本序列: max_length =128 input_txt ="""In a shocking finding, scientist discovered a herd of unicorns living in a remote,...
parser.add_argument("--max_length",type=int,default=2048) parser.add_argument("--load_in_8bit",action='store_true') parser.add_argument("--dtype",type=str,default="float16") parser.add_argument("--with_conf",action='store_true') ...
模型生成了一段随机的文本, PreTrainedModel.generate() 的默认参数可以在Pipelines 中直接覆盖,比如下面的max_length。 from transformers import pipeline text_generator = pipeline("text-generation") print(text_generator("As far as I am concerned, I will", max_length=50, do_sample=False)) [{'genera...
Retrieval](https://arxiv.org/abs/2010.00904).synced_gpus(`bool`,*optional*,defaults to`False`):Whether tocontinuerunning thewhileloop untilmax_length(neededforZeRO stage3)kwargs:Ad hoc parametrizationof`generate_config`and/or additional model-specific kwargs that will be ...