You are a machine learning engineer tasked with deploying a machine learning model to a mobile device for real-time object detection. The model currently performs well but is too large to fit within the device's memory and computational constraints. To ensure the model can run efficiently on the device without sacrificing too much accuracy, you need to reduce its size. Given these constraints, which combination of techniques is the MOST LIKELY to effectively reduce the model’s size while maintaining acceptable performance?