Update README.md

README.md

@@ -6,9 +6,11 @@ license: apache-2.0
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-BLING-1.4b-0.1 is the first model release in the BLING ("Best Little Instruction-following No-GPU-required") model series, designed as custom instruct-following laptop-effective GPT decoder-based models (~1B-2.7B parameters). 
+BLING-1.4b-0.1 is the first model release in the BLING ("Best Little Instruction-following No-GPU-required") model series.
 
-BLING models are fine-tuned with distilled high-quality custom instruct datasets, targeted at a specific subset of instruct tasks with the objective of providing a high-quality Instruct model that can be run entirely without a GPU server, with good quality instruct-following capability that can be loaded and run locally on a laptop even without using any quantization optimizations.
+BLING models are fine-tuned with distilled high-quality custom instruct datasets, targeted at a specific subset of instruct tasks with 
+the objective of providing a high-quality Instruct model that is 'inference-ready' on a CPU laptop even 
+without using any advanced quantization optimizations.
 
 ### Model Description
 
@@ -29,7 +31,8 @@ The intended use of BLING models is two-fold:
 1.  Provide a high-quality Instruct models that can run on a laptop for local testing.  We have found it extremely useful when building a
    proof-of-concept, or working with sensitive enterprise data that must be closely guarded, especially in RAG use cases.
 
-2.  Push the state of the art for smaller Instruct-following models in the 1B - 7B range through improved fine-tuning datasets and targeted "instruction" tasks.
+2.  Push the state of the art for smaller Instruct-following models in the sub-7B parameter range, especially 1B-3B, as single-purpose
+    automation tools for specific tasks through targeted fine-tuning datasets and focused "instruction" tasks.
 
 
 ### Direct Use
@@ -42,7 +45,8 @@ legal and regulatory industries with complex information sources.  Rather than t
 BLING is ideal for rapid prototyping, testing, and the ability to perform an end-to-end workflow locally on a laptop without
 having to send sensitive information over an Internet-based API.
 
-The first BLING models have been trained on question-answering, key-value extraction, and basic summarization as the core instruction types.
+The first BLING models have been trained for common RAG scenarios, specifically:   question-answering, key-value extraction, and basic summarization as the core instruction types
+without the need for a lot of complex instruction verbiage - provide a text passage context, ask questions, and get clear fact-based responses.
 
 
 ### Out-of-Scope Use