Update README.md

README.md

@@ -6,51 +6,29 @@ tags: [green, llmware-rag, p1, ov]
 
 # bling-tiny-llama-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.    
-
-[**bling-tiny-llama**](https://huggingface.co/llmware/bling-tiny-llama-v0) is a fact-based question-answering model, optimized for complex business documents.  
-
-Get started right away
-
-1.  Install dependencies
-
-  ```
-  pip3 install llmware
-  pip3 install openvino
-  pip3 install openvino_genai
-  ```
-
-2.  Hello World
-
-  ```
-  from llmware.models import ModelCatalog
-  model = ModelCatalog().load_model("bling-tiny-llama-ov")
-  response = model.inference("The stock price is $45.\nWhat is the stock price?")
-  print("response: ", response)
-  ```
-    
-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)    
+**bling-tiny-llama-ov** is a very small, very fast fact-based question-answering model, optimized for complex business documents, and 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 series, e.g., llmware/bling-phi-3-ov.  
 
 ### Model Description
 
 - **Developed by:** llmware  
 - **Model type:** tinyllama  
-- **Parameters:** 1.1 billion
+- **Parameters:** 1.1 billion  
+- **Quantization:** int4  
 - **Model Parent:** llmware/bling-tiny-llama-v0  
 - **Language(s) (NLP):** English  
 - **License:** Apache 2.0  
-- **Uses:** Fact-based question-answering  
+- **Uses:** Fact-based question-answering, RAG  
 - **RAG Benchmark Accuracy Score:** 86.5  
-- **Quantization:** int4  
-  
 
-## Model Card Contact
+    
+Get started right away with [OpenVino](https://github.com/openvinotoolkit/openvino)  
+
+Looking for AI PC solutions, contact us at [llmware](https://www.llmware.ai)    
 
-[llmware on hf](https://www.huggingface.co/llmware)  
 
+## Model Card Contact  
+
+[llmware on hf](https://www.huggingface.co/llmware)  
 [llmware website](https://www.llmware.ai)