Bert Model 训练遇到的问题描述_exception: model "bert-base-uncased" on the hub do

1. tokenizer.encode() 方法 与 tokenizer.tokenize() 之间的区别：
(1) tokenizer.encode() 返回其在字典中的id

(2) tokenizer.tokenize() 返回 token

def bert_():
    model_name = 'bert-base-chinese'
    MODEL_PATH = 'F:/models/bert-base-chinese/'
 
    # a.通过词典导入分词器
    tokenizer = BertTokenizer.from_pretrained(model_name)
    # b. 导入配置文件
    model_config = BertConfig.from_pretrained(model_name)
    # 修改配置
    model_config.output_hidden_states = True
    model_config.output_attentions = True
    # 通过配置和路径导入模型
    bert_model = BertModel.from_pretrained(MODEL_PATH, config=model_config)
    # tokenizer.encode()
    sen_code_encode = tokenizer.encode("自然语")
    print("sen_code_encode",sen_code)
    # tokenizer.tokenize
    sen_code_tokenizer = tokenizer.tokenize("自然语")
    print("sen_code_tokenizer", sen_code0)
 
if __name__ == '__main__':
    bert_()