Update README.md

README.md

@@ -6,9 +6,9 @@ tags: [green, llmware-rag, p3, ov]
 
 # bling-phi-3-ov
 
-**bling-phi-3-ov** is a fast and accurate fact-based question-answering model, designed for retrieval augmented generation (RAG) with complex business documents, and quantized and packaged in OpenVino int4 for AI PCs using Intel GPU, CPU and NPU.    
+**bling-phi-3-ov** is a fast and accurate 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 most accurate in the BLING/DRAGON model series, which is especially notable given the relativlye small size and is ideal for use on AI PCs and local inferencing.  
+This model is one of the most accurate in the BLING/DRAGON model series, which is especially notable given the relatively small size and is ideal for use on AI PCs and local inferencing.  
 
 ### Model Description
 
@@ -23,11 +23,6 @@ This model is one of the most accurate in the BLING/DRAGON model series, which i
 - **RAG Benchmark Accuracy Score:** 99.5
 
     
-Get started right away with [OpenVino](https://github.com/openvinotoolkit/openvino)  
-
-Looking for AI PC solutions, contact us at [llmware](https://www.llmware.ai)    
-
-
 ## Model Card Contact  
 [llmware on github](https://www.github.com/llmware-ai/llmware)  
 [llmware on hf](https://www.huggingface.co/llmware)