Update README.md

README.md

@@ -23,7 +23,7 @@ With Red Hat AI you can,
 - Leverage quantized variants of the leading open source models such as Llama, Mistral, Granite, DeepSeek, Qwen, Gemma, Phi, and many more. 
 - Tune smaller, purpose-built models with your own data.
 - Quantize your models with [LLM Compressor](https://github.com/vllm-project/llm-compressor) or use our pre-optimized models on HuggingFace.
-- Optimize inference with [vLLM](https://github.com/vllm-project/vllm) across any hardware and deployment scenario.
+- Optimize inference with [vLLM](https://github.com/vllm-project/vllm) across any hardware and deployment scenarios.
 
 We provide accurate model checkpoints compressed with SOTA methods ready to run in vLLM such as W4A16, W8A16, W8A8 (int8 and fp8), and many more! 
 If you would like help quantizing a model or have a request for us to add a checkpoint, please open an issue in https://github.com/vllm-project/llm-compressor.