Update app.py

app.py

@@ -17,6 +17,13 @@ app_examples = [
     ["O tempo está ensolarado hoje, perfeito para um passeio no parque."]
 ]
 
+model_list = [
+    "knowhate/HateBERTimbau",
+    "knowhate/HateBERTimbau-youtube",
+    "knowhate/HateBERTimbau-twitter",
+    "knowhate/HateBERTimbau-yt-tt",
+]
+
 user_friendly_name = {
     "knowhate/HateBERTimbau": "HateBERTimbau (Original)",
     "knowhate/HateBERTimbau-youtube": "HateBERTimbau (YouTube)",
@@ -32,11 +39,9 @@ user_friendly_name_list = list(user_friendly_name.values())
 #demo.launch()
 
 def predict(text, chosen_model):    
-
-    chosen_model_name = reverse_user_friendly_name[chosen_model]
     
     # Initialize the pipeline with the chosen model
-    model_pipeline = pipeline("text-classification", model=chosen_model_name)
+    model_pipeline = pipeline("text-classification", model=reverse_user_friendly_name[chosen_model])
     result = model_pipeline(text)
     label = result[0]['label']