Update app.py

app.py

@@ -43,7 +43,17 @@ user_friendly_name_list = list(user_friendly_name.values())
 #demo = gr.Interface.from_pipeline(pipe)
 #demo.launch()
 
-predict = ["1", "Hate Speech"]
+def predict(s1, chosen_model):
+    # Get model name from user-friendly name
+    full_chosen_model_name = 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
+
+    return scores
 
 inputs = [
     gr.Textbox(label="Text", value=app_examples[0][0]),