fix code

app.py

@@ -19,8 +19,6 @@ transformer_model = TFAutoModel.from_pretrained("xlm-roberta-base") #philschmid/
 max_seq_length = 32
 
 def create_model():
-  # input_layer = Input(shape=(input_ids.shape[1],))
-  # embedding_layer = Embedding(max_seq_length+ 1, 200, input_length=max_seq_length)(input_layer)
 
   inputs = tf.keras.layers.Input(shape=(max_seq_length,), dtype=tf.int32)
   embedding_layer = transformer_model(inputs)[0]
@@ -66,9 +64,9 @@ def create_model():
   output_layer3 = Dense(1, activation='sigmoid', name='output3')(x3) 
   output_layer4 = Dense(1, activation='sigmoid', name='output4')(x4) 
   output_layer5 = Dense(1, activation='sigmoid', name='output5')(x5) 
-  output_layer6 = Dense(num_class_label_6, activation='softmax', name='output6')(x6) 
-  output_layer7 = Dense(num_class_label_7, activation='softmax', name='output7')(x7) 
-  output_layer8 = Dense(num_class_label_8, activation='softmax', name='output8')(x8) 
+  output_layer6 = Dense(119, activation='softmax', name='output6')(x6) 
+  output_layer7 = Dense(25, activation='softmax', name='output7')(x7) 
+  output_layer8 = Dense(61, activation='softmax', name='output8')(x8) 
 
   model = Model(inputs=inputs , outputs=[output_layer1, output_layer2, output_layer3,output_layer4,output_layer5,output_layer6,output_layer7,output_layer8])
   model.load_weights("t1_m1.h5")