请使用与'Bert'相关的分词器类和与'Nezha'相关的模型类

NEZHA: Neural Contextualized Representation for Chinese Language Understanding 魏俊秋，任晓哲，李晓光，黄文勇，廖艺，王亚生，林家树，江鑫，陈晓和刘群

原始检查点可以在 here 找到

示例用法

from transformers import BertTokenizer, NezhaModel
tokenizer = BertTokenizer.from_pretrained('sijunhe/nezha-cn-base')
model = NezhaModel.from_pretrained("sijunhe/nezha-cn-base")
text = "我爱北京天安门"
encoded_input = tokenizer(text, return_tensors='pt')
output = model(**encoded_input)