TensorFlow SavedModel
TensorFlow SavedModel is a universal serialization format for TensorFlow models that captures the complete model architecture, weights, and computation graph in a single directory. It enables saving and loading models across different TensorFlow versions and platforms, supporting both training and inference workflows. This format is the recommended way to export models for deployment in production environments, such as TensorFlow Serving, TensorFlow Lite, or TensorFlow.js.
Developers should use TensorFlow SavedModel when they need to save trained models for reuse, sharing, or deployment, as it ensures compatibility and reproducibility. It is essential for deploying models to cloud services, mobile devices, or web applications, and for versioning models in machine learning pipelines. Use cases include exporting models after training, loading pre-trained models for fine-tuning or inference, and integrating with TensorFlow's ecosystem tools like TFX (TensorFlow Extended).