Update README.md

README.md

@@ -8,8 +8,7 @@ license: apache-2.0
 
 dragon-mistral-7b-v0 part of the dRAGon ("Delivering RAG On ...") model series, RAG-instruct trained on top of a Mistral-7B base model.
 
-DRAGON models are fine-tuned with high-quality custom instruct datasets, designed for production quality use in RAG scenarios.
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+DRAGON models have been fine-tuned with the specific objective of fact-based question-answering over complex business and legal documents with an emphasis on reducing hallucinations and providing short, clear answers for workflow automation.
 
 ### Benchmark Tests  
 
@@ -36,19 +35,6 @@ For test run results (and good indicator of target use cases), please see the fi
 - **License:** Apache 2.0
 - **Finetuned from model:** Mistral-7B-Base
 
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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-The intended use of DRAGON models is two-fold:
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-1.  Provide high-quality RAG-Instruct models designed for fact-based, no "hallucination" question-answering in connection with an enterprise RAG workflow.
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-2.  DRAGON models are fine-tuned on top of leading base foundation models, generally in the 6-7B+ range, and purposefully rolled-out across multiple base models to provide choices and "drop-in" replacements for RAG specific use cases.
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-3.  DRAGON models were trained on the same principles as the BLING models, so generally, it should be easy to "upgrade" from a BLING model in testing to a DRAGON model in production.
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-
 ### Direct Use
 
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->