Update app.py

app.py

@@ -17,13 +17,6 @@ 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)",
@@ -38,8 +31,10 @@ user_friendly_name_list = list(user_friendly_name.values())
 #demo = gr.Interface.from_pipeline(pipe)
 #demo.launch()
 
-def predict(text, chosen_model):
+def predict(text, chosen_model_name):    
 
+    chosen_model = reverse_user_friendly_name[chosen_model_name]
+    
     # Initialize the pipeline with the chosen model
     model_pipeline = pipeline("text-classification", model=chosen_model)
     result = model_pipeline(text)