Update README.md

README.md

@@ -3,13 +3,13 @@ license: apache-2.0
 inference: false 
 ---
 
-# bling-tiny-llama-ov
+# dolphin-2.9.3-mistral-7b-32k-ov
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-**bling-tiny-llama-ov** is an OpenVino int4 quantized version of BLING Tiny-Llama 1B, providing a very fast, very small inference implementation, optimized for AI PCs using Intel GPU, CPU and NPU.    
+**dolphin-2.9.3-mistral-7b-32k-ov** is an OpenVino int4 quantized version of Dolphin 2.9.3 Mistral 7B, providing a very fast, very small inference implementation, optimized for AI PCs using Intel GPU, CPU and NPU.    
 
-[**bling-tiny-llama**](https://huggingface.co/llmware/bling-tiny-llama-v0) is a fact-based question-answering model, optimized for complex business documents.  
+[**llmware/dolphin-2.9.3-mistral-7b-32k**](https://huggingface.co/cognitivecomputations/dolphin-2.9.3-mistral-7b-32k-ov) is a leading dialog chat finetune of Mistral 7B.  
 
 Get started right away with [OpenVino](https://github.com/openvinotoolkit/openvino) 
 
@@ -18,14 +18,14 @@ Looking for AI PC solutions and demos, contact us at [llmware](https://www.llmwa
 
 ### Model Description
 
-- **Developed by:** llmware  
-- **Model type:** tinyllama  
-- **Parameters:** 1.1 billion
-- **Model Parent:** llmware/bling-tiny-llama-v0  
+- **Developed by:** cognitivecomputations
+- **Model type:** mistral
+- **Parameters:** 7 billion
+- **Model Parent:** cognitivecomputations/dolphin-2.9.3-mistral-7b-32k-ov  
 - **Language(s) (NLP):** English  
 - **License:** Apache 2.0  
-- **Uses:** Fact-based question-answering  
-- **RAG Benchmark Accuracy Score:** 86.5  
+- **Uses:** General purpose dialog and chat 
+- **RAG Benchmark Accuracy Score:** NA
 - **Quantization:** int4