Update app.py

app.py

@@ -10,9 +10,9 @@ model = T5ForConditionalGeneration.from_pretrained('deep-learning-analytics/Gram
 def correct_grammar(input_text,num_return_sequences=1):
   batch = tokenizer([input_text],truncation=True,padding='max_length',max_length=64, return_tensors="pt").to(torch_device)
   translated = model.generate(**batch,max_length=64,num_beams=2, num_return_sequences=num_return_sequences, temperature=1.5)
-  tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)[0]
+  tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)
   return tgt_text
   
 if text:
-  result = correct_grammar(text)
+  result = correct_grammar(text)[0]
   st.json(result)