Update README.md

README.md

@@ -23,7 +23,7 @@ Average of 2 Test Runs with 1 point for correct answer, 0.5 point for partial co
 --Boolean:  85.0%  
 --Math/Logic:  82.5%  
 --Complex Questions (1-5):  3 (Above Average - multiple-choice, causal)  
---Summarization Quality (1-5):  3 (Coherent, extractive)  
+--Summarization Quality (1-5):  3 (Above Average)  
 --Hallucinations:  No hallucinations observed in test runs.  
 
 For test run results (and good indicator of target use cases), please see the files ("core_rag_test" and "answer_sheet" in this repo).
@@ -35,7 +35,7 @@ For test run results (and good indicator of target use cases), please see the fi
 - **Developed by:** llmware
 - **Model type:** Phi-2B
 - **Language(s) (NLP):** English
-- **License:** Microsoft Research License
+- **License:** [Microsoft Research License](https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE)
 - **Finetuned from model:** Microsoft Phi-2B-Base
 
 ## Uses
@@ -69,7 +69,7 @@ Any model can provide inaccurate or incomplete information, and should be used i
 
 ## How to Get Started with the Model
 
-The fastest way to get started with dRAGon is through direct import in transformers:
+The fastest way to get started with BLING is through direct import in transformers:
 
     from transformers import AutoTokenizer, AutoModelForCausalLM  
     tokenizer = AutoTokenizer.from_pretrained("bling-phi-2-v0", trust_remote_code=True)