Update app.py

app.py

@@ -323,16 +323,17 @@ if (should_train_model=='1'): #train model
     
     if response.status_code == 200:
         data = response.json()  # Convert response to JSON
-        print(data)
+        print("print data from API: ", data)
     else:
         print(f"Error: {response.status_code}")
-    else:
-        print('Load Pre-trained')
-        model_save_path = f"./{model_save_path}_model"
-        tokenizer_save_path = f"./{model_save_path}_tokenizer"
-        # RobertaTokenizer.from_pretrained(model_save_path)
-        model = AutoModelForSequenceClassification.from_pretrained(model_save_path).to('cpu')
-        tokenizer = AutoTokenizer.from_pretrained(tokenizer_save_path)
+        
+else:
+    print('Load Pre-trained')
+    model_save_path = f"./{model_save_path}_model"
+    tokenizer_save_path = f"./{model_save_path}_tokenizer"
+    # RobertaTokenizer.from_pretrained(model_save_path)
+    model = AutoModelForSequenceClassification.from_pretrained(model_save_path).to('cpu')
+    tokenizer = AutoTokenizer.from_pretrained(tokenizer_save_path)
 
 #Define the label mappings (this must match the mapping used during training)
 label_mapping = model.config.label_mapping