Update app.py

app.py

@@ -32,16 +32,10 @@ model_list = [
 #demo = gr.Interface.from_pipeline(pipe)
 #demo.launch()
 
-def predict(s1, chosen_model):
-    # Get model name from user-friendly name
-    full_chosen_model_name = chosen_model
+def predict(chosen_model):
 
     # Initialize the pipeline with the chosen model
-    model_pipeline = pipeline("text-classification", model=full_chosen_model_name)
-
-    # Perform inference on the input text
-    predicted_label = model_pipeline(s1)[0]  # Assuming your model returns a single prediction
-
+    predicted_label = pipeline("text-classification", model=chosen_model)
     return predicted_label
 
 inputs = [