Update README.md

README.md

@@ -40,7 +40,7 @@ _/  |_ _______ |__|_____     ____    ____   __ __ |  |   __ __   _____
 
 Triangulum 1B is a collection of pretrained and instruction-tuned generative models, designed for multilingual applications. These models are trained using synthetic datasets based on long chains of thought, enabling them to perform complex reasoning tasks effectively.
 
-# **Key Features**
+# **Key Features & Model Architecture**
 
 - **Foundation Model**: Built upon LLaMA's autoregressive language model, leveraging an optimized transformer architecture for enhanced performance.
 
@@ -48,6 +48,10 @@ Triangulum 1B is a collection of pretrained and instruction-tuned generative mod
 
 - **Multilingual Support**: Designed to handle multiple languages, ensuring broad applicability across diverse linguistic contexts.
 
+---
+
+- Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
+
 # **Training Approach**
 
 1. **Synthetic Datasets**: Utilizes long chain-of-thought synthetic data to enhance reasoning capabilities.