Right now, the Kernel Explainer sends data batches to the model for prediction as those data batches are created, meaning it sends ~2000 requests by default to the model. These are really slow when going from Java -> Python -> Java. Instead, collect batches in Java and send them all together once to Python, where they can batch processed if necessary and then re-aggregated.