transformers/models/auto/tokenization_auto.py get_tokenizer_config 调用 cached_file, 得到 resolved_config_file 为 tokenizer_config.json 读取为 json 格式 (tokenizer_config) {"eos_token":"","model_max_length":512,"name_or_path":"xxx","pad_token":"<pad>","separate_vocabs":false,"source_la...
model_max_length=1000000000000000019884624838656, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': '<unk>'}, clean_up_tokenization_spaces=False), added_tokens_decoder={ 0: AddedToken("<unk>", rstrip=False,...
model = AutoModelForCausalLM.from_pretrained("gpt2")# 编码输入文本,增加返回的张量 input_text ="The meaning of life is" input_ids = tokenizer.encode(input_text, return_tensors='pt')# 生成文本 output = model.generate(input_ids, max_length=50)# 解码生成的文本 decoded_output = tokenizer.d...
model, tokenizer, model_name = "unsloth/llama-2-7b-bnb-4bit", model_max_length = 4096, padding_side = "right", token = None, _reload = True, ): # Checks tokenizer for out of bounds ids. # Mainly a fix for https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha ...
from_pretrained("bert-base-uncased") # 将英文文本转换为token IDs,并进行其他必要的处理 text = "Hello, I am a transformer model." encoded_input = tokenizer.encode_plus( text, add_special_tokens=True, # 返回特殊tokens(这个下面会讲到) max_length=20, # 生成语句的最大长度 padding="max_...
defcall(self,inputs):print(type(inputs))print(inputs)tokenized=tokenizer.batch_encode_plus(inputs,add_special_tokens=True,return_tensors='tf',max_length=self._maxlength,padding='max_length',truncation=True)returntokenized defbuild_classifier_model():text_input=tf.keras.layers.Input(shape=(),...
近日，PyTorch 社区又添入了「新」工具，包括了更新后的 PyTorch 1.2，torchvision 0.4，torchaudio 0.3 和 torchtext 0.4。每项工具都进行了新的优化与改进，兼容性更强，使用起来也更加便捷。PyTorch 发布了相关文章介绍了每个工具的更新细节，AI 开发者将其整理与编译如下。最近...
在Python代码中,你需要从modelscope库中导入AutoModelForCausalLM类。正确的导入方式如下: python from modelscope import AutoModelForCausalLM 注意,导入时类名应该保持大小写一致,即AutoModelForCausalLM而不是automodelforcausallm。 3. 从modelscope库中导入AutoTokenizer 同样地,你也需要从modelscope库中导入Auto...
args.max_len, ) 开发者ID:microsoft,项目名称:unilm,代码行数:21,代码来源:preprocess.py 示例2: get_defaults ▲点赞 7▼ # 需要导入模块: from transformers import AutoTokenizer [as 别名]# 或者: from transformers.AutoTokenizer importfrom_pretrained[as 别名]defget_defaults(self, model, tokenizer, ...
def __init__(self, model_name_or_path: str, max_seq_length: int = 128, model_args: Dict = {}, cache_dir: Optional[str] = None ): super(Transformer, self).__init__() self.config_keys = ['max_seq_length'] self.max_seq_length = max_seq_length config = AutoConfig.from_pret...