short form to Full form

app.py

@@ -43,18 +43,18 @@ def predict_abusive_lang(text):
         prediction = model.predict(text)
         print("prediction ", prediction)
         if len(prediction)!=0 and prediction[0]==0:
-            return ["NA", cleaned_text]
+            return ["Not Abusive", cleaned_text]
         elif len(prediction)!=0 and prediction[0]==1:
-            return ["AB",cleaned_text]
+            return ["Abusive",cleaned_text]
         else :
             return ["Please write something in the comment box..","No cleaned text"]
     elif lang=='hi':
         print("using transformers for Hindi text")
         scores = predict_hindi_text(text)
         if scores[1] > scores[0]:  # If score for abusive class is higher
-            return ["AB", text]
+            return ["Abusive", text]
         else:
-            return ["NA", text]
+            return ["Not Abusive", text]
     else:
         return ["UN","No cleaned text"]