Update app.py

app.py

@@ -35,8 +35,8 @@ model_list = [
 def predict(text, target, chosen_model):    
     model1 = tf.keras.models.load_model(chosen_model, custom_objects={"TFBertModel": TFBertModel})
     checkpoint = "neuralmind/bert-base-portuguese-cased"
-    tokenizer = AutoTokenizer.from_pretrained(checkpoint, use_fast=True)
-    tokpair = tokenizer(text, target, truncation=True, padding='max_length', return_tensors='np')
+    tokenizer = AutoTokenizer.from_pretrained(checkpoint, use_fast=True, model_max_length=512)
+    tokpair = tokenizer(text, target, truncation=True, padding='max_length', return_tensors='np', return_token_type_ids=False)
     
     outp = model1(tokpair)