Update README.md

README.md

@@ -12,6 +12,24 @@ BLING models are fine-tuned with distilled high-quality custom instruct datasets
 the objective of providing a high-quality Instruct model that is 'inference-ready' on a CPU laptop even 
 without using any advanced quantization optimizations.
 
+### **PERFORMANCE on BASIC RAG TEST DATASET** 
+							
+| Model                 |  Params (B) |	Sourcing |	GPU/CPU	 | Output Tokens | Out as % of Input | Process Time (secs) | Score (0-100) |
+| :----------           | :--------:  |  :----:  | :-----:   | :---------:   | :-------:         | :--------:          | :-------:     |
+| gpt-4	                |   <=1000	  | Closed   | Multi-GPU | 2665	         | 10.53%	         | 183.8	           |    100        |
+| gpt-3.5-turbo-instruct|	<=175	  | Closed	 | Multi-GPU |	2621	     | 11.49%	         | 62.7	               |    100        |
+| claude-instant-v1	    |   <=50	  | Closed	 | Multi-GPU |	6337	     | 26.50%	         |  154	               |    100        |
+| aib-read-gpt	        |   7	      | Closed   | GPU	     |  1964	     |  9.30%            |	114	               |     96        |
+| **bling_falcon-1b-0.1**	|   **1.3**	      | **Open**	 | **CPU**	     |  **3204**	     | **14.55%**         |  **696**               |     **77**        |
+| bling_pythia-1.4b-0.1	|   1.4	      | Open	 | CPU	     |  2589	     | 11.75%	         |  593.5	           |     65        |
+| bling_pythia-1b-0.1	|   1.0	      | Open     |	CPU	     | 2753	         | 12.49%	         |  428	               |     59        |
+| bling_cerebras-1.3b   |	1.3	      | Open     |	CPU	     | 3202	         | 20.01%	         |  690.1	           |     52        |
+| bling_pythia_410m	    |  0.41	      |  NA	     |  CPU	     |  2349	     |  10.66%	         |  189	               |     36        |
+| bling_cerebras_590m	|  0.59	      |  NA	     |  CPU	     |  4407	     |   20.01%	         |  400.8	           |     30        |  
+
+For more details on this evaluation, please see the dataset: **llmware/rag_instruct_test_dataset_0.1** and [BLOG](https://medium.com/@darrenoberst/evaluating-llm-performance-in-rag-instruct-use-cases-083dc272a31d)  
+
+
 ### Model Description
 
 <!-- Provide a longer summary of what this model is. -->