pipe=pipeline(model="facebook/opt-1.3b",device_map="auto",model_kwargs={"load_in_8bit":True})output=do_sample=True,top_p=0.95) 畅享全文阅读体验
#第5章/文本生成fromtransformersimportpipelinetext_generator=pipeline("text-generation")text_generator("As far as I am concerned, I will",max_length=50,do_sample=False) 在这段代码中,得到了 text_generator 对象后,直接接调用 text_generator 对象,入参为一个句子的开头,让 text_generator 接着往下续写...
# pip install accelerate bitsandbytesimporttorchfromtransformersimportpipelinepipe=pipeline(model="facebook/opt-1.3b",device_map="auto",model_kwargs={"load_in_8bit":True})output=pipe("This is a cool example!",do_sample=True,top_p=0.95) 请注意,您可以将checkpoint替换为任何支持大型模型加载...
pipeline = transformers.pipeline( "text-generation", model=model, torch_dtype=torch.float16, device_map="auto", ) sequences = pipeline( 'I liked "Breaking Bad" and "Band of Brothers". Do you have any recommendations of other shows I might like?\n', do_sample=True, top_k=10, num_r...
("As far as I am concerned, I will", max_length=50, do_sample=False) from transformers import pipeline # 命名实体识别 ner_pipe = pipeline("ner") sequence = """Hugging Face Inc. is a company based in New York City. Its headquarters are in DUMBO, therefore very close to the ...
例如令牌的概率如下所示: 例如,Pancakes + looks时间段1的概率等效于: Pancakes looks so = log...
pipeline = transformers.pipeline( "text-generation", model="codellama/CodeLlama-7b-hf", torch_dtype=torch.float16, device_map="auto", ) sequences = pipeline( 'def fibonacci(', do_sample=True, temperature=0.2, top_p=0.9, num_return_sequences=1, ...
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)) [{'generated_text': 'As far as I am concerned, I will be the first to admit that I am not a fan of the idea...
如果可用,我们还会将模型加载到 GPU 上,否则加载到 CPU 上。 pipeline() 随后将根据需要将所有输入/...
2. 使用 Pipeline 进行推理 pipeline()函数是使用预训练模型进行推理的最简单方式。它能够跨不同模态处理...