Update app.py

app.py

@@ -1,4 +1,5 @@
 from transformers import BertTokenizer, BertModel
+from transformers import pipeline
 import gradio as grad
 
 model_name = "MiVaCod/rotten"
@@ -6,11 +7,16 @@ text2text_tkn= BertTokenizer.from_pretrained(model_name)
 mdl = BertModel.from_pretrained(model_name)
 
 def text2text_paraphrase(sentence1):
-     inp1 = sentence1
-     enc = text2text_tkn(inp1, return_tensors="pt")
-     tokens = mdl.generate(**enc)
-     response=text2text_tkn.batch_decode(tokens)
-     return response
+    classifier = pipeline('text-classification', model='MiVaCod/rotten')
+    res = classifier(sentence1)
+
+    clase = res[0]
+    if res=='LABEL_0':
+        res = 'BAD!'
+    else:
+        res = 'GOOD!'
+    
+    return res
 
 sent1=grad.Textbox(lines=1, label="Review", placeholder="Introduce la review de una película.")
 out=gr.outputs.Label(num_top_classes=1)