Update README.md

README.md

@@ -9,12 +9,12 @@ tags:
 - nef
 - solo-developer
 - bangladesh-ai
-- 1b-parameters
+- 2b-parameters
 pipeline_tag: text-generation
 library_name: pytorch
 ---
 
-# Hexa-1B — NEF Serialization Prototype
+# Hexa-2B — NEF Serialization Prototype
 
 **Founder:** Madhab — Engineering Student, Cox's Bazar, Bangladesh  
 **Organization:** Hexa Innovate  
@@ -25,7 +25,7 @@ library_name: pytorch
 
 ## What This Is
 
-Hexa-1B is a 1.1-billion parameter language model built as a **technical proof-of-concept for the NEF serialization framework**. The goal of this release is singular: demonstrate that NEF can correctly serialize, store, and load a billion-scale model on accessible hardware without dependency on standard bloated AI libraries.
+Hexa-2B is a 2-billion parameter language model built as a **technical proof-of-concept for the NEF serialization framework**. The goal of this release is singular: demonstrate that NEF can correctly serialize, store, and load a billion-scale model on accessible hardware without dependency on standard bloated AI libraries.
 
 This is not a general-purpose chat model. Inference quality is intentionally deferred to the production training run. What this prototype proves is the infrastructure layer — and that is the point.
 
@@ -51,7 +51,7 @@ NEF is a custom serialization framework built from scratch to replace the overhe
 | Property | Detail |
 |---|---|
 | Architecture | HexaDense (Transformer Decoder) |
-| Parameters | 1.1 Billion |
+| Parameters | 2 Billion (0.27B active via MoE) |
 | Serialization | NEF (Neural Essence Format) |
 | Training hardware | Dual NVIDIA Tesla T4 (cloud compute credits) |
 | Languages | English, Bengali |
@@ -94,7 +94,7 @@ I am a Diploma in Engineering student from Cox's Bazar, Bangladesh. Every compon
 
 Most billion-parameter models come from large teams with large budgets. This one did not. The constraint was the design brief.
 
-Hexa-1B is the foundation. The production model is next.
+Hexa-2B is the foundation. The production model is next.
 
 ---