updated params in predict() function

app.py

@@ -61,14 +61,14 @@ explainer = LimeTextExplainer(class_names = class_names)
 def predict_and_explainations(model_choice, user_text):
     tokenizer, model, id2label = load_model_and_tokenizer(model_choice)
     
-    input = tokenizer(user_text, return_tensors = "tf", truncation = True, padding = True, max_length = 128)
+    input = tokenizer(user_text, return_tensors = "tf", truncation = True, padding = "max_length", max_length = 128)
     logits = model(**input).logits
     probs = tf.nn.softmax(logits, axis = -1).numpy()[0]
     predicted_index = tf.argmax(probs).numpy()
     predictions = {id2label[i] : float(probs[i]) for i in range(len(probs))}
     
     def lime_predict(texts):
-        batch = tokenizer(texts, return_tensors = "tf", padding = True, max_length = 128)
+        batch = tokenizer(texts, return_tensors = "tf", padding = "max_length", max_length = 128)
         logits = model(**batch).logits
         lime_output = tf.nn.softmax(logits, axis = 1).numpy()
         return lime_output