use the correct tokenizer

app.py

@@ -38,7 +38,7 @@ def feedback(text):
     num_return_sequences=1
     batch =  grammar_tokenizer([text],truncation=True,padding='max_length',max_length=64, return_tensors="pt")
     corrections= grammar_model.generate(**batch,max_length=64,num_beams=2, num_return_sequences=num_return_sequences, temperature=1.5)
-    corrected_text = tokenizer.decode(corrections[0], clean_up_tokenization_spaces=True, skip_special_tokens=True)
+    corrected_text = grammar_tokenizer.decode(corrections[0], clean_up_tokenization_spaces=True, skip_special_tokens=True)
     print("The corrections are: ", corrections)
     if corrected_text == text:
         feedback = f'Looks good! Keep up the good work'