Update README.md

README.md

@@ -1,21 +1,21 @@
 ---
 license: apache-2.0
 inference: false 
-tags: [green, p1, llmware-fx, ov]
+tags: [green, p1, llmware-fx, ov, emerald]
 ---
 
-# slim-extract-tiny-ov
+# slim-extract-tiny-ov  
 
-<!-- Provide a quick summary of what the model is/does. -->
+**slim-extract-tiny-ov** is a specialized function calling model with a single mission to look for values in a text, based on an "extract" key that is passed as a parameter.  No other instructions are required except to pass the context passage, and the target key, e.g., 
 
-**slim-extract-tiny-ov** is an OpenVino int4 quantized version of slim-extract-tiny, providing a very fast, very small inference implementation, optimized for AI PCs using Intel GPU, CPU and NPU.    
+  text_passage = "The company announced that for the current quarter the total revenue increased by 9% to $125 million."
 
-[**slim-extract-tiny**](https://huggingface.co/llmware/slim-extract-tiny) is a specialized extraction function calling model that looks for a key and value in a complex business document and returns a python dictionary with the designated key and the values found in the text for that key.  
+  llm_response = model.function_call(text_passage, function="extract", params=["revenue"])
 
+  Output: `llm_response = {"revenue": [$125 million"]}`
+  
 
-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 an OpenVino int4 quantized version of slim-extract-tiny, providing a very fast, very small inference implementation, optimized for AI PCs using Intel GPU, CPU and NPU.    
 
 
 ### Model Description
@@ -33,6 +33,8 @@ Looking for AI PC solutions and demos, contact us at [llmware](https://www.llmwa
 
 ## 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)