Keras SavedModel and TensorFlow Lite: Interoperability for Low-Traffic Serverless Inference
Deployment Backend Selection for Sporadic Keras Inference When a tf.keras model receives only occasional inference requests, the deployment target determines whether idle compute costs dominate the budget. The interoperability boundary between a Keras SavedModel and downstream runtimes—TensorFlow Serving, TensorFlow Lite, and ONNX Runtime—presents an unresol
keras