Update README.md

README.md

@@ -17,8 +17,8 @@ To easily get started with the model, you can use our newly introduced ONNX Runt
 ## ONNX Models 
 Here are some of the optimized configurations we have added:
 
-1. ONNX model for int4 CPU and Mobile: ONNX model for CPU and mobile using int4 quantization via RTN.
-2. ONNX model for int4 CUDA GPU using int4 quantization via RTN.
+1. ONNX model for CPU and mobile using int4 quantization via RTN.
+2. ONNX model for GPU using int4 quantization via RTN.
 
 
 ## Performance
@@ -34,8 +34,17 @@ ONNX enables you to run your models on-device across CPU, GPU, NPU. With ONNX yo
 |deepseek-ai_DeepSeek-R1-Distill-Qwen-7B|	ONNX |	Int4/bfloat16 |	CPU |	CPU	Intel i9 |	3.184 |	20X |
 |deepseek-ai_DeepSeek-R1-Distill-Qwen-1.5B|	ONNX |	Int4 |	CPU |	CPU	Intel i9 |	11.749 |	1.4x  |
 
-CUDA BUILD SPECS: Onnxruntime-genai-cuda==0.6.0-dev, transformers==4.46.2, onnxruntime-gpu==1.20.1
-CPU BUILD SPECS: Onnxruntime-genai==0.6.0-dev, transformers==4.46.2, onnxruntime==1.20.01
+CPU build specs:
+
+- onnxruntime-genai==0.6.0-dev
+- transformers==4.46.2
+- onnxruntime==1.20.01
+
+CUDA build specs:
+
+- onnxruntime-genai-cuda==0.6.0-dev
+- transformers==4.46.2
+- onnxruntime-gpu==1.20.1
 
 
 ## Model Description
@@ -48,5 +57,6 @@ CPU BUILD SPECS: Onnxruntime-genai==0.6.0-dev, transformers==4.46.2, onnxruntime
 - **Disclaimer:** Model is only an optimization of the base model, any risk associated with the model is the responsibility of the user of the model. Please verify and test for you scenarios. There may be a slight difference in output from the base model with the optimizations applied. **
 
 ## Base Model Information
+
 See HF links [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B/) and [DeepSeek-R1-Distill-Qwen-7B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B/) for details.