Update README.md

README.md

@@ -17,7 +17,7 @@ base_model:
 pipeline_tag: text-generation
 ---
 
-[Phi4-mini](https://huggingface.co/microsoft/Phi-4-mini-instruct) quantized with [torchao](https://huggingface.co/docs/transformers/main/en/quantization/torchao) int4 weight only quantization, using [hqq](https://mobiusml.github.io/hqq_blog/) algorithm for improved accuracy, by PyTorch team.
+[Phi4-mini](https://huggingface.co/microsoft/Phi-4-mini-instruct) quantized with [torchao](https://huggingface.co/docs/transformers/main/en/quantization/torchao) int4 weight only quantization, using [hqq](https://mobiusml.github.io/hqq_blog/) algorithm for improved accuracy, by PyTorch team. Use it directly or serve using [vLLM](https://docs.vllm.ai/en/latest/) for 67% VRAM reduction and 12-20% speedup on A100 GPUs.
 
 # Quantization Recipe
 
@@ -149,8 +149,6 @@ lm_eval --model hf --model_args pretrained=pytorch/Phi-4-mini-instruct-int4wo-hq
 
 # Peak Memory Usage
 
-We can use the following code to get a sense of peak memory usage during inference:
-
 ## Results
 
 | Benchmark        |                |                                |