调用tokenizer_class_from_name 这里实际执行了 module=importlib.import_module(f".marian",transformers.models)returngetattr(module,"MarianTokenizer") getattr(module, "MarianTokenizer") 传递给了 tokenizer_class, 最后 from_pretrained 这里可以开始看 tokenization_marian.py 的代码 :transformers/models/marian/tok...
return tokenizer_class_py.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs) File "/home/faith/miniconda3/envs/torch/lib/python3.7/site-packages/transformers/tokenization_utils_base.py", line 1653, in from_pretrained resolved_vocab_files, pretrained_model_name_or_path, init_con...
Even if we try to override the from_pretrained func to use tqdm to download the model into assigned path, it will still report error at request line like: ('Connection aborted.', ConnectionResetError(10054, monetjoe changed the title tokenizer = AutoTokenizer.from_pretrained('distilroberta-base...
由于众所周知的原因,国内很难使用huggingface去下载权重,但现在的大模型的权重以及相关的分词器配置都放在huggingface的仓库中。当我们使用AutoTokenizer.from_pretrained去载入相关分词器和模型时,会访问huggingface自动下载模型。但随着大模型的发布,很多模型的tokenizer都以tokenizer.model的方式保存,并且使用自己的.py文件去...
def __init__( self, model_name="bert-base-cased", to_lower=False, custom_tokenize=None, cache_dir=".", ): self.model_name = model_name self.tokenizer = AutoTokenizer.from_pretrained( model_name, do_lower_case=to_lower, cache_dir=cache_dir, output_loading_info=False, ) self.do_...
# 需要导入模块: from transformers import AutoTokenizer [as 别名]# 或者: from transformers.AutoTokenizer importfrom_pretrained[as 别名]defseg(args):tokenizer = AutoTokenizer.from_pretrained( args.model_name_or_path, do_lower_case=True) seg_file( ...
from tokenizers import (decoders, models, normalizers, pre_tokenizers, processors, trainers, Tokenizer, ) tokenizer = AutoTokenizer.from_pretrained("bert-base-cased",cache_dir='D:\\temp\\huggingface\\chen\\datasets') example = "My name is Sylvain and I work at Hugging Face in Brooklyn也就...
model_name="dbmdz/bert-base-italian-xxl-cased"tokenizer=AutoTokenizer.from_pretrained(model_name)bert=TFBertModel.from_pretrained(model_name) 该模型将提供一系列意大利推文,并需要确定它们是否具有讽刺意味。 我在构建模型的初始部分时遇到了问题,该部分接受输入并将它们输入到令牌程序,以便获得我可以提供给BERT...
model = AutoModel.from_pretrained('your_model_name') tokenizer = AutoTokenizer.from_pretrained...
tokenization_auto.py in from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs) 190 config = kwargs.pop("config", None) 191 if not isinstance(config, PretrainedConfig): --> 192 config = AutoConfig.from_pretrained(pretrained_model_name_or_path, **kwargs) 193 194 if "...