Test the BERT model for Chinese simulation embedding

+import os
+from transformers.models.bert import BertTokenizer, BertModel
+import torch
+
+class BERT_CTM_Model:
+    def __init__(self, bert_model_path):
+        # 加载BERT模型和tokenizer
+        self.tokenizer = BertTokenizer.from_pretrained(bert_model_path)
+        self.model = BertModel.from_pretrained(bert_model_path)
+
+    def get_bert_embeddings(self, text):
+        """使用BERT模型生成文本的嵌入向量"""
+        inputs = self.tokenizer(text, return_tensors="pt", padding="max_length", truncation=True, max_length=80)
+        with torch.no_grad():
+            outputs = self.model(**inputs)
+        return outputs.last_hidden_state.cpu().numpy()  # [batch_size, sequence_length, hidden_size]
+
+if __name__ == "__main__":
+    model = BERT_CTM_Model('./bert_model')
+    text = "这是一个测试文本"
+    embedding = model.get_bert_embeddings(text)
+    print(embedding.shape)