Update README.md

README.md

@@ -12,10 +12,7 @@ tags: [green, llmware-rag, p1,ov]
 
 [**bling-qwen-500m**](https://huggingface.co/llmware/bling-qwen-500m) is a fact-based question-answering model, optimized for complex business documents. 
 
-Get started right away with [OpenVino](https://github.com/openvinotoolkit/openvino) 
-
-Looking for AI PC solutions and demos, contact us at [llmware](https://www.llmware.ai) 
-
+This is the smallest instruct trained model from the Qwen2 series, and offers reasonable accuracy given its small size. For more accurate models, select a larger model in this series. 
 
 ### Model Description
 
@@ -26,12 +23,14 @@ Looking for AI PC solutions and demos, contact us at [llmware](https://www.llmwa
 - **Language(s) (NLP):** English 
 - **License:** Apache 2.0 
 - **Uses:** Fact-based question-answering 
-- **RAG Benchmark Accuracy Score:** [80]
+- **RAG Benchmark Accuracy Score:** 81.0 
 - **Quantization:** int4 
  
 
 ## Model Card Contact
 
+[llmware on github](https://www.github.com/llmware-ai/llmware) 
+
 [llmware on hf](https://www.huggingface.co/llmware) 
 
 [llmware website](https://www.llmware.ai)