# 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( os.path.join(args.output_dir, args.data_split ...
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_...
There are 3 listed ways this error can be caused. I'm not sure which my case falls under. Section 1.3: # define the tokenizertokenizer=AutoTokenizer.from_pretrained(configs.output_dir,do_lower_case=configs.do_lower_case) Traceback:
首先，我必须pip install sentencepiece。然而，在同一代码行中，我得到了sentencepiece的错误。在两个参数...
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后来了解到这里还有一个问题是RWKV的世界模型系列的tokenizer是自定义的，在Huggingface里面并没有与之对应...
看一个程序 #include <iostream> using namespace std; class A { public: virtual void Fun(int...