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 ...

“model_name”: “llama_3_1”, “model_type”: “transformer”, “num_layers”: 12, “hidden_size”: 768, “num_heads”: 12, “vocab_size”: 32000 ...

Google announced the first major release for TensorFlow ... TF Serving 1.0 introduced the concept of a MetaGraph, which contains information about the processor architecture a trained model ...

Google has released TensorFlow Serving to the open-source community ... deploy new models and run experiments on the same server architecture and API, and works best with TensorFlow integration.

TFRT Architecture - source ... Google integrated TFRT with TensorFlow Serving, a production-grade serving environment for model inference. For their experiment, they chose a ResNet-50 model ...