tokenizer_config = get_tokenizer_config(pretrained_model_name_or_path, **kwargs) 内部将使用 cached_file 函数读取path文件tokenizer_config.json;然后再解析json文件;输出为tokenizer_config; # 找到./chatglm-6b\tokenizer_config.json resolved_config_file = cached_file(pretrained_model_name_or_path,......
tokenizer = AutoTokenizer.from_pretrained(tokenizer_type) 后面可以通过from_pretrained函数中的retrained_model_name_or_path()方法,指定路径或者模型名称来加载对应的分词器。 文档给的实例 tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased') # Download vocabulary from S3 and cache. tokenizer = Au...
)classBertTokenizer(Tokenizer):def__init__(self,config:Dict[Text, Any] = None)->None:""" :param config: {"pretrained_model_name_or_path":"", "cache_dir":"", "use_fast":""} """super().__init__(config)self.tokenizer = AutoTokenizer.from_pretrained( config["pretrained_model_name...
BertTokenizer.from_pretrained是 Hugging Face's Transformers 库中的一个方法,用于从预训练模型中加载相应的分词器(tokenizer)。这个方法接受以下参数: 1.pretrained_model_name_or_path:预训练模型的名字或路径。这可以是一个模型名称(如 'bert-base-uncased'),一个模型文件的路径,或者一个包含模型配置和权重文件...
public static final LexicalTokenizerName NGRAM Tokenizes the input into n-grams of the given size(s). See http://lucene.apache.org/core/4\_10\_3/analyzers-common/org/apache/lucene/analysis/ngram/NGramTokenizer.html.PATH_HIERARCHY public static final LexicalTokenizerName PATH_HIER...
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...
将hugging face的权重下载到本地，然后我们之后称下载到本地的路径为llama_7b_localpath【python 3.6】...
#请问下载的模型和分词器是放在如图上放置吗,还缺什么文件吗,model_config.json里的tokenizer_type这里修改为/home/root1/data/glm/VisualGLM-6B/THUDM/visualglm-6b(这是我图上的路径),tokenizer_config.json里的name_or_path也一样修改对吗? Sign up for free to join this conversation on GitHub. Already...
LlamaTokenizerFast(name_or_path='mistralai/Mistral-7B-Instruct-v0.3', vocab_size=32768, model_max_length=1000000000000000019884624838656, is_fast=True, padding_side='left', truncation_side='right', special_tokens={'bos_token': '', 'eos_token': '', 'unk_token': '<unk>'}, clean_up_tok...
model_path –path to sentence piece tokenizer model. To create the model use create_spt_model() special_tokens –either list of special tokens or dictionary of token name to token value legacy –when set to True, the previous behavior of the SentecePiece wrapper will be restored, including ...