Update app.py

app.py

@@ -51,7 +51,7 @@ embeddings, patent_numbers, metadata, texts = load_data()
 try:
     tokenizer = AutoTokenizer.from_pretrained('anferico/bert-for-patents')
     bert_model = AutoModel.from_pretrained('anferico/bert-for-patents')
-    word_embedding_model = models.Transformer(model_name='anferico/bert-for-patents', tokenizer=tokenizer, model=bert_model)
+    word_embedding_model = models.Transformer(model_name='anferico/bert-for-patents', tokenizer=tokenizer)
     pooling_model = models.Pooling(word_embedding_model.get_word_embedding_dimension())
     model = SentenceTransformer(modules=[word_embedding_model, pooling_model])
 except Exception as e: