Update app.py

app.py

@@ -5,7 +5,7 @@ st.write("Paste or type text, submit and the machine will attempt to correct you
 
 default_text = "This should working"
 sent = st.text_area("Text", default_text, height=40)
-num_correct_options = st.number_input('Number of Correction Options', min_value=1, max_value=2, value=1, step=1)
+num_correct_options = st.number_input('Number of Correction Options', min_value=1, max_value=3, value=1, step=1)
 
 from transformers import T5ForConditionalGeneration, T5Tokenizer
 import torch
@@ -15,7 +15,7 @@ model = T5ForConditionalGeneration.from_pretrained('deep-learning-analytics/Gram
 
 def correct_grammar(input_text, num_return_sequences=num_correct_options):
   batch = tokenizer([input_text], truncation=True, padding = 'max_length', max_length = 64, return_tensors = 'pt').to(torch_device)
-  results = model.generate(**batch, max_length = 64, num_beams = 3, num_return_sequences = num_correct_options, temperature = 1.5)
+  results = model.generate(**batch, max_length = 64, num_beams = 4, num_return_sequences = num_correct_options, temperature = 1.5)
   
   return results