Upload README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+inference: false 
+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)    
+
+
+### Model Description
+
+- **Developed by:** llmware  
+- **Model type:** tinyllama  
+- **Parameters:** 1.1 billion
+- **Model Parent:** llmware/bling-tiny-llama-v0  
+- **Language(s) (NLP):** English  
+- **License:** Apache 2.0  
+- **Uses:** Fact-based question-answering  
+- **RAG Benchmark Accuracy Score:** 86.5  
+- **Quantization:** int4  
+  
+
+## Model Card Contact
+
+[llmware on hf](https://www.huggingface.co/llmware)  
+
+[llmware website](https://www.llmware.ai)