Update 'main' post-24.02 (#36)

Co-authored-by: Olga Andreeva <[email protected]>

Author: mc-nv

README.md

@@ -28,12 +28,6 @@
 
 [![License](https://img.shields.io/badge/License-BSD3-lightgrey.svg)](https://opensource.org/licenses/BSD-3-Clause)
 
-**LATEST RELEASE: You are currently on the main branch which tracks
-under-development progress towards the next release. The current release branch
-is [r24.01](https://github.com/triton-inference-server/vllm_backend/tree/r24.01)
-and which corresponds to the 24.01 container release on
-[NVIDIA GPU Cloud (NGC)](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/tritonserver).**
-
 # vLLM Backend
 
 The Triton backend for [vLLM](https://github.com/vllm-project/vllm)
@@ -81,7 +75,14 @@ script.
 
 A sample command to build a Triton Server container with all options enabled is shown below. Feel free to customize flags according to your needs.
 
+Please use [NGC registry](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/tritonserver/tags)
+to get the latest version of the Triton vLLM container, which corresponds to the
+latest YY.MM (year.month) of [Triton release](https://github.com/triton-inference-server/server/releases).
+
+
 ```
+# YY.MM is the version of Triton.
+export TRITON_CONTAINER_VERSION=<YY.MM>
 ./build.py -v  --enable-logging
                 --enable-stats
                 --enable-tracing
@@ -96,9 +97,9 @@ A sample command to build a Triton Server container with all options enabled is
                 --endpoint=grpc
                 --endpoint=sagemaker
                 --endpoint=vertex-ai
-                --upstream-container-version=24.01
-                --backend=python:r24.01
-                --backend=vllm:r24.01
+                --upstream-container-version=${TRITON_CONTAINER_VERSION}
+                --backend=python:r${TRITON_CONTAINER_VERSION}
+                --backend=vllm:r${TRITON_CONTAINER_VERSION}
 ```
 
 ### Option 3. Add the vLLM Backend to the Default Triton Container