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README.md

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-* **Model size: 3.21B parameters**
-
-# **V2**
-
-**This version is a further fine-tuned version of Llama-3.2-3B-Instruct with a slightly larger dataset and more epochs.**
-
-**The V2 version performs better in multiple benchmarks than the V1 version, and even outmatches both 1211 and V1 in mathematics: https://huggingface.co/MultivexAI/Gladiator-Mini-Exp-1221-3B-Instruct**
-
-**Examples:**
-----------------
-**MATH**
-**1211: 13.44 %**
-**V1: 13.07 %**
-**V2: 13.75 %**
-----------------
-----------------
-**IFEval**
-**V1: 60.79 %**
-**V2: 62.15 %**
-----------------
-----------------
-**BBH**
-**V1: 20.40 %** 
-**V2: 20.65 %**
-----------------
+## Gladiator-Mini-Exp-1221-3B-Instruct - V2: Enhanced Performance
+
+**This is V2, an improved iteration of our Gladiator-Mini-Exp-1221-3B-Instruct model, fine-tuned from Llama-3.2-3B-Instruct with a slightly expanded dataset and increased training epochs.**
+
+**Major Improvements in V2:**
+
+*   **Superior Performance:** V2 demonstrates enhanced performance across multiple benchmarks compared to V1.
+*   **Mathematics Boost:** Notably, V2 surpasses both the 1211 model and V1 in mathematical reasoning, as evidenced by the MATH benchmark results below.
+*   **Model Size:** 3.21 Billion parameters
+
+**Benchmark Highlights:**
+
+| Benchmark | 1211      | V1        | V2        |
+| :-------- | :-------- | :-------- | :-------- |
+| **MATH**  | **13.44%** | **13.07%** | **13.75%** |
+| IFEval    |           | 60.79%    | 62.15%    |
+| BBH       |           | 20.40%    | 20.65%    |
+
+[Link to V1](https://huggingface.co/MultivexAI/Gladiator-Mini-Exp-1221-3B-Instruct)
+
+**In summary, V2 offers a noticeable performance upgrade over V1, particularly in mathematical tasks. Explore the model and experience the improvements!**
+
 # Gladiator-Mini-exp-1221-Instruct
 
 **Gladiator-Mini-exp-1221** is a 3-billion parameter language model focused on **complex reasoning**. Built upon the foundation of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct), this experimental model is designed to explore what's achievable with smaller models in analytical thinking. It's all about pushing boundaries and learning what's possible in resource-efficient AI. We believe small models represent the future of open source language models, making AI more accessible and adaptable for a wider range of users and applications.