docs: add TensorFlow 2.21 SageMaker training to README release notes (#6381)

Add the TensorFlow v2.21.0 (SageMaker training, Amazon Linux 2023, Python
3.12; GPU on CUDA 12.9.1) release highlight and drop the oldest entry
(vLLM v0.23.0) to keep the list at 7. Tags and packaging details sourced
from the 2.21 SageMaker docs data files.

Co-authored-by: Bhanu Teja Goshikonda <bhanugk@amazon.com>

Author: bhanutejagk

README.md

@@ -28,14 +28,14 @@ ______________________________________________________________________
 
 ### 🚀 Release Highlights
 
+- **[2026/07/10]** [TensorFlow v2.21.0 (SageMaker training)](https://gallery.ecr.aws/deep-learning-containers/tensorflow-training) — SageMaker CPU: `2.21.0-cpu-py312-amzn2023-sagemaker` · SageMaker GPU: `2.21.0-gpu-py312-cu129-amzn2023-sagemaker` · Amazon Linux 2023 with Python 3.12; GPU images ship CUDA 12.9.1.
 - **[2026/07/06]** [SGLang Server v1.2 (AL2023)](https://gallery.ecr.aws/deep-learning-containers/sglang) — EC2: `server-cuda-v1.2` · SageMaker: `server-sagemaker-cuda-v1.2` · SGLang `0.5.14`; adds support for the NVIDIA LocateAnything-3B vision-grounding model and upgrades sgl-kernel 0.4.4, FlashInfer 0.6.12, Mooncake 0.3.11.post1, NCCL 2.30.4, and EFA 1.49.0.
 - **[2026/07/02]** [vLLM Server v2.1 (AL2023)](https://gallery.ecr.aws/deep-learning-containers/vllm) — EC2: `server-cuda-v2.1` · SageMaker: `server-sagemaker-cuda-v2.1` · vLLM `0.24.0`; adds JetBrains Mellum2-12B-A2.5B-Thinking (`MellumForCausalLM`); FlashInfer 0.6.12; drops the `transformers<5.10` pin (now requires transformers ≥ 5.5.3).
 - **[2026/07/02]** [vLLM-Omni v1.4 (AL2023)](https://gallery.ecr.aws/deep-learning-containers/vllm) — EC2: `omni-cuda-v1.4` · SageMaker: `omni-sagemaker-cuda-v1.4` · SageMaker `/v1/videos` and `/v1/videos/sync` accept `application/json` again (JSON→multipart conversion restored); no framework bump (vLLM-Omni 0.21.0rc1).
 - **[2026/07/02]** [PyTorch v2.12.1](https://gallery.ecr.aws/deep-learning-containers/pytorch) — EC2: `2.12.1-cu130-amzn2023` · SageMaker: `2.12.1-cu130-amzn2023-sagemaker` · Amazon Linux 2023 with EFA, flash-attn, and Transformer Engine; PyTorch 2.12.1 bug-fix release (B200/Triton correctness fixes).
 - **[2026/07/01]** [vLLM v0.24.0](https://gallery.ecr.aws/deep-learning-containers/vllm) — EC2: `0.24.0-gpu-py312-ec2` · SageMaker: `0.24.0-gpu-py312` · MiniMax-M3, DiffusionGemma (+CPU), Hierarchical Reasoning Model, OpenMOSS; streaming parser engine (Qwen3, MiniMax-M2, GLM-4.7/5.1/5.2, Nemotron V3); DeepSeek-V4 fixes.
 - **[2026/06/29]** [SGLang Server v1.1 (AL2023)](https://gallery.ecr.aws/deep-learning-containers/sglang) — EC2: `server-cuda-v1.1` · SageMaker: `server-sagemaker-cuda-v1.1` · SGLang `0.5.13`; adds NIXL KV connector for prefill/decode disaggregation and `runai-model-streamer[s3,gcs,azure]` for fast weight streaming from object storage; starlette CVE patch.
 - **[2026/06/29]** [SGLang v0.5.14](https://gallery.ecr.aws/deep-learning-containers/sglang) — EC2: `0.5.14-gpu-py312-ec2` · SageMaker: `0.5.14-gpu-py312` · GLM 5.2, LiquidAI LFM2.5, Kimi-K2.7-Code, DeepSeek V4 on GB300.
-- **[2026/06/14]** [vLLM v0.23.0](https://gallery.ecr.aws/deep-learning-containers/vllm) — EC2: `0.23.0-gpu-py312-ec2` · SageMaker: `0.23.0-gpu-py312` · Step-3.7-Flash, Cosmos3 Reasoner, Gemma 4 Unified (encoder-free), Granite Speech Plus, Cohere Mini Code; Anthropic Messages API structured output.
 
 ### 📢 Support Updates