Advanced features on TensorFlow Serving

Wei Wei, Developer Advocate at Google, shares several advanced TensorFlow Serving features (experimental). Learn how TF Serving can tend JAX models, serve non-TensorFlow models with new servables, and remotely predict RPC with distributed serving.

Resources:
TF Serving model server parameters → https://goo.gle/3tQ99Qq
Intro to JAX: Accelerating Machine Learning research → https://goo.gle/3xOKBsq
Convert JAX models to SavedModel with jax2tf → https://goo.gle/3NiCCtk
Convert JAX models to TFLite → https://goo.gle/3Ngqo4n
Creating a new kind of servable → https://goo.gle/3A1xuqq
XGBoost Serving using TF Serving (community project) → https://goo.gle/3A08iAO
Hashmap servable reference on Github → https://goo.gle/3HUy4bp
TensorFlow servable on Github → https://goo.gle/3xOZScG
Remote predict TensorFlow operator → https://goo.gle/3Nim5pl

Deploying Production ML Models with TensorFlow Serving playlist → https://goo.gle/tf-serving
Subscribe to TensorFlow → https://goo.gle/TensorFlow

#TensorFlow #MachineLearning #ML

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