Update app.py

app.py

@@ -8,7 +8,7 @@ tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
 # Function to correct sentences
-def correct_sentence(sentence):
+def predict(sentence):
     inputs = tokenizer.encode("correction: " + sentence, return_tensors="pt", max_length=512, truncation=True)
     outputs = model.generate(inputs, max_length=128, num_beams=4, early_stopping=True)
     corrected_sentence = tokenizer.decode(outputs[0], skip_special_tokens=True)