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README.md

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 OpenMath2-Llama3.1-8B is obtained by finetuning [Llama3.1-8B-Base](https://huggingface.co/meta-llama/Llama-3.1-8B) with [OpenMathInstruct-2](https://huggingface.co/datasets/nvidia/OpenMathInstruct-2).
 
-The model outperforms [Llama3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on popular math benchmarks, especially on [MATH](https://github.com/hendrycks/math) by 15.9%. 
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+The model outperforms [Llama3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on all the popular math benchmarks we evaluate on, especially on [MATH](https://github.com/hendrycks/math) by 15.9%. 
+
+<!-- <p align="center">
+  <img src="scaling_plot.jpg" width="350"><img src="math_level_comp.jpg" width="350">
+</p> -->
+
+  <style>
+      .image-container {
+          display: flex;
+          justify-content: center;
+          align-items: center;
+          gap: 20px;
+      }
+      .image-container img {
+          width: 350px;
+          height: auto;
+      }
+  </style>
+
+<div class="image-container">
+        <img src="scaling_plot.jpg" title="Performance of Llama-3.1-8B-Instruct as it is trained on increasing proportions of OpenMathInstruct-2">
+        <img src="math_level_comp.jpg" title="Comparison of OpenMath2-Llama3.1-8B vs. Llama-3.1-8B-Instruct across MATH levels">
+    </div>
 
 | Model | GSM8K | MATH | AMC 2023 | AIME 2024 | Omni-MATH |
 |:---|:---:|:---:|:---:|:---:|:---:|