Update app.py

app.py

@@ -17,7 +17,7 @@ tokenizer = T5Tokenizer.from_pretrained('deep-learning-analytics/GrammarCorrecto
 model = T5ForConditionalGeneration.from_pretrained('deep-learning-analytics/GrammarCorrector').to(torch_device)
 
 def correct_grammar(input_text,num_return_sequences=num_return_sequences):
-  batch = tokenizer([input_text],truncation=True,padding='max_length',max_length=64, return_tensors="pt").to(torch_device)
+  batch = tokenizer([input_text],truncation=True, return_tensors="pt").to(torch_device)
   results = model.generate(**batch,num_beams=2, num_return_sequences=num_return_sequences, temperature=1.5)
   #answer = tokenizer.batch_decode(results[0], skip_special_tokens=True)
   return results