Update README.md

README.md

@@ -1,26 +1,26 @@
 ---
 license: apache-2.0
 inference: false 
-tags: [green, llmware-rag, p1, ov]
+tags: [green, llmware-rag, p7, ov, emerald]
 ---
 
-# bling-tiny-llama-ov
+# dragon-mistral-ov
 
-**bling-tiny-llama-ov** is a very small, very fast fact-based question-answering model, designed for retrieval augmented generation (RAG) with complex business documents, quantized and packaged in OpenVino int4 for AI PCs using Intel GPU, CPU and NPU. 
+**dragon-mistral-ov** is a high-quality fact-based question-answering model, designed for retrieval augmented generation (RAG) with complex business documents, quantized and packaged in OpenVino int4 for AI PCs using Intel GPU, CPU and NPU. 
 
-This model is one of the smallest and fastest in the series. For higher accuracy, look at larger models in the BLING/DRAGON series. 
+This model provides a good combination of quality and inference speed. 
 
 ### Model Description
 
 - **Developed by:** llmware 
-- **Model type:** tinyllama 
-- **Parameters:** 1.1 billion 
+- **Model type:** mistral-0.1
+- **Parameters:** 7 billion 
 - **Quantization:** int4 
-- **Model Parent:** [llmware/bling-tiny-llama-v0](https://www.huggingface.co/llmware/bling-tiny-llama-v0) 
+- **Model Parent:** [llmware/dragon-mistral-7b-v0](https://www.huggingface.co/llmware/dragon-mistral-7b-v0) 
 - **Language(s) (NLP):** English 
 - **License:** Apache 2.0 
 - **Uses:** Fact-based question-answering, RAG 
-- **RAG Benchmark Accuracy Score:** 86.5 
+- **RAG Benchmark Accuracy Score:** 96.5 
 
 
 ## Model Card Contact