model outputs dict

app.py

@@ -24,7 +24,7 @@ if description and review:
     batch_dict = tokenizer(input_texts, max_length=512,
                            padding=True, truncation=True, return_tensors='pt')
 
-    query_embedding, doc_embedding = model(**batch_dict).pooler_output
+    query_embedding, doc_embedding = model(**batch_dict, return_dict=True).pooler_output
 
     similarity = torch.nn.functional.cosine_similarity(
         query_embedding, doc_embedding)