Google has just moved to a production release of TensorFlow Serving, its open source library for serving machine-learned models in production environments. A beta version of the technology was released in February.

Part of Google’s TensorFlow machine intelligence project, the TensorFlow Serving 1.0 library is intended to aid the deployment of algorithms and experiments while maintaining the same server architecture and APIs. TensoFlow Serving lets you push out multiple versions of models over time, as well as roll them back.

The library of course integrates with TensorFlow learning models, but it can also be extended to serve other model types.

A pre-built binary is available for the software. A Docker container can be used to install the server binary on non-Linux systems.

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