Update app.py

app.py

@@ -1,11 +1,13 @@
 import gradio as gr
 from transformers import pipeline
+import spaces
 
 # Load the models using pipeline
 audio_model = pipeline("audio-classification", model="MelodyMachine/Deepfake-audio-detection-V2")
 image_model = pipeline("image-classification", model="dima806/deepfake_vs_real_image_detection")
 
 # Define the prediction function
+@spaces.GPU
 def predict(audio, image, model_choice):
     print("Data received:", audio if model_choice == "Audio Deepfake Detection" else image)  # Debugging statement
     try:
@@ -26,6 +28,7 @@ def predict(audio, image, model_choice):
         return {"error": str(e)}
 
 # Update interface based on the selected model
+@spaces.GPU
 def update_interface(model_choice):
     if model_choice == "Audio Deepfake Detection":
         return gr.update(visible=True), gr.update(visible=False)