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A complete containerized setup for Triton inference server and its python client using a realistic pre-trained XGBoost classifier model.
Triton backend is difficult for a client to use whether it's sending by rest-api or grpc. If the client wants to customize the request body then this repository would like to offer a sidecar along with rest-api and triton client on Kubernetes.
QuickStart for Deploying a Basic Model on the Triton Inference Server