serving
A flexible, high-performance serving system for machine learning models
About this project
TensorFlow Serving TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. It deals with the inference aspect of machine learning, taking models after training and managing their lifetimes, providing clients with versioned access via a high-performance, reference-counted lookup table. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data. To note a few features: — Can serve multiple models, or multiple versions of the same model simultaneously — Exposes both gRPC as well as HTTP inference endpoints — Allows…
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