Update README.md

README.md

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 ## Overview
 
-Welcome to the next evolution of AI reasoning! Reason-With-Choice-3B is not just another fine-tuned model, it’s a game-changer. It doesn't just generate reasoning, it chooses whether reasoning is even necessary before delivering an answer. This self-reflective capability allows it to introspect, analyze, and adapt to the complexity of each question, ensuring the most efficient and insightful response possible.
+Welcome to the next evolution of AI reasoning! Reason-With-Choice-3B is not just another fine-tuned model, it's a game-changer. It doesn't just generate reasoning, it chooses whether reasoning is even necessary before delivering an answer. This self-reflective capability allows it to introspect, analyze, and adapt to the complexity of each question, ensuring the most efficient and insightful response possible.
 
 Think about it: most AI models blindly generate reasoning even when unnecessary, leading to bloated, redundant responses. Not this one. With its built-in decision-making, Reason-With-Choice-3B determines if deep reasoning is needed or if a direct answer will suffice—bringing unparalleled efficiency and intelligence to your AI-driven applications.
 
 ## Key Highlights
 - Reasoning & Self-Reflection: The model first decides if reasoning is necessary and then either provides step-by-step logic or directly answers the question.
-- Structured Output: Responses follow a strict format with <think>, <reflection>, and <answer> sections, ensuring clarity and interpretability.
+- Structured Output: Responses follow a strict format with `<think>`, `<reflection>`, and `<answer>` sections, ensuring clarity and interpretability.
 - Optimized Training: Trained using GRPO (Guided Reward Policy Optimization) to enforce structured responses and improve decision-making.
 - Efficient Inference: Fine-tuned with Unsloth & Hugging Face’s TRL, ensuring faster inference speeds and optimized resource utilization.