Update README.md

README.md

@@ -15,13 +15,12 @@ EdgeRunner-Tactical-7B is a 7 billion parameter language model that delivers pow
 
 ## Highlights
 
-- 7 billion parameters
-- SOTA performance for its size
-- Initialized from Qwen2-Instruct
-- Applied Self-Play Preference Optimization ([SPPO](https://arxiv.org/abs/2405.00675)) for continuous training on Qwen2-Instruct
-- Competitive performance with Mixtral-8x7B, Meta Llama-3-70B on several benchmarks.
-- Supports a context length of 128K tokens, making it ideal for tasks requiring many conversation turns or working with large amounts of text
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+- 7 billion parameters that balance power and efficiency
+- SOTA performance within the 7B model range
+- Initialized from Qwen2-Instruct, leveraging prior advancements
+- Self-Play Preference Optimization (SPPO) applied for continuous training and alignment
+- Competitive performance on several benchmarks with Meta’s Llama-3-70B, Mixtral 8x7B, and Yi 34B
+- Context length of 128K tokens, ideal for extensive conversations and large-scale text tasks
 
 ## Quickstart