Update app.py

app.py

@@ -34,15 +34,13 @@ model_name = "MiVaCod/mbart-neutralization"
 text2text_tkn= MBart50Tokenizer.from_pretrained(model_name)
 mdl = T5ForConditionalGeneration.from_pretrained(model_name)
 
-def text2text_paraphrase(sentence1,sentence2):
+def text2text_paraphrase(sentence1):
      inp1 = "rte sentence1: "+sentence1
-     inp2 = "sentence2: "+sentence2
-     combined_inp=inp1+" "+inp2
-     enc = text2text_tkn(combined_inp, return_tensors="pt")
+     enc = text2text_tkn(inp1, return_tensors="pt")
      tokens = mdl.generate(**enc)
      response=text2text_tkn.batch_decode(tokens)
      return response
 
 sent1=grad.Textbox(lines=1, label="Frase misógina", placeholder="Introduce una frase misógina")
 out=grad.Textbox(lines=1, label="Frase corregida")
-grad.Interface(text2text_paraphrase, inputs=[sent1,sent2], outputs=out).launch()
+grad.Interface(text2text_paraphrase, inputs=[sent1], outputs=out).launch()