fix error

app.py

@@ -14,8 +14,8 @@ from transformers import TFAutoModel, AutoTokenizer
 from sklearn.model_selection import train_test_split
 
 # load the tokenizer and transformer model
-tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-base",max_length=60) #xlm-roberta-base bert-base-multilingual-cased
-transformer_model = TFAutoModel.from_pretrained("xlm-roberta-base") #philschmid/tiny-bert-sst2-distilled
+tokenizer = AutoTokenizer.from_pretrained("nlptown/flaubert_small_cased_sentiment",max_length=60) #xlm-roberta-base bert-base-multilingual-cased
+transformer_model = TFAutoModel.from_pretrained("nlptown/flaubert_small_cased_sentiment") #philschmid/tiny-bert-sst2-distilled
 max_seq_length = 32
 
 def create_model():
@@ -88,30 +88,30 @@ def predict(text):
   predicted_labels = model.predict(test_padded_sequences)
 
   for i in range(len(test_texts)):
-  print(test_texts[i])
-  valid = 1 if predicted_labels[0][i] > 0.5 else 0
-  is_scene = 1 if predicted_labels[1][i] > 0.5 else 0
-  has_num = 1 if predicted_labels[2][i] > 0.5 else 0
-  print(f'is_valid : {valid}')
-  print(f'is_scene : {is_scene}')
-  print(f'has_num : {has_num}')
-
-  turn = 1 if predicted_labels[3][i] > 0.5 else 0
-  print(f'turn_on_off : {turn}')
-  print(f'device : ไฟ')
-
-  env_id = np.argmax(predicted_labels[5][i])
-  env_label = env_decode[env_id]
-
-  hour_id = np.argmax(predicted_labels[6][i])
-  hour_label = hour_decode[hour_id]
-
-  minute_id = np.argmax(predicted_labels[7][i])
-  minute_label = minute_decode[minute_id]
-  print(f'env : {env_label}')
-  print(f'hour : {hour_label}')
-  print(f'minute : {minute_label}')
-  print('----')
+    print(test_texts[i])
+    valid = 1 if predicted_labels[0][i] > 0.5 else 0
+    is_scene = 1 if predicted_labels[1][i] > 0.5 else 0
+    has_num = 1 if predicted_labels[2][i] > 0.5 else 0
+    print(f'is_valid : {valid}')
+    print(f'is_scene : {is_scene}')
+    print(f'has_num : {has_num}')
+
+    turn = 1 if predicted_labels[3][i] > 0.5 else 0
+    print(f'turn_on_off : {turn}')
+    print(f'device : ไฟ')
+
+    env_id = np.argmax(predicted_labels[5][i])
+    env_label = env_decode[env_id]
+
+    hour_id = np.argmax(predicted_labels[6][i])
+    hour_label = hour_decode[hour_id]
+
+    minute_id = np.argmax(predicted_labels[7][i])
+    minute_label = minute_decode[minute_id]
+    print(f'env : {env_label}')
+    print(f'hour : {hour_label}')
+    print(f'minute : {minute_label}')
+    print('----')
   return 'hello'
 
 iface = gr.Interface(