import numpy as np
from bert4keras.backend import keras, K
from bert4keras.models import build_transformer_model
from bert4keras.tokenizers import Tokenizer
from bert4keras.snippets import AutoRegressiveDecoder

# nezha配置
config_path = './nezha_gpt_dialog/config.json'
checkpoint_path = './nezha_gpt_dialog/model.ckpt'
dict_path = './nezha_gpt_dialog/vocab.txt'

# 建立分词器
tokenizer = Tokenizer(dict_path, do_lower_case=True)

# 建立并加载模型
model = build_transformer_model(
    config_path,    
  checkpoint_path,    
  model='nezha',    
  application='lm',)

model.summary()