Update README.md

README.md

@@ -14,25 +14,36 @@ license: openrail++
 
 # OBS-Diff Structured Pruning for Stable Diffusion-xl-base-1.0 
 
-<table>
-  <tr>
-    <td width="30%">
-      <img src="teaser.jpg" alt="OBS-Diff" width="100%" />
-    </td>
-    <td width="70%">
-      <h4>✂️ <a href="https://alrightlone.github.io/OBS-Diff-Webpage/">OBS-Diff: Accurate Pruning for Diffusion Models in One-Shot</a></h4>
-      <p>
-        <em><b>Junhan Zhu</b>, Hesong Wang, Mingluo Su, Zefang Wang, Huan Wang*</em>
-        <br>
-        <a href="https://arxiv.org/abs/2510.06751"><img src="https://img.shields.io/badge/Preprint-arXiv-b31b1b.svg?style=flat-square"></a> 
-        <a href="https://github.com/Alrightlone/OBS-Diff"><img src="https://img.shields.io/github/stars/Alrightlone/OBS-Diff?style=flat-square&logo=github"></a>
-      </p>
-      <p>
-        The <b>first training-free, one-shot pruning framework</b> for Diffusion Models, supporting diverse architectures and pruning granularities. Uses Optimal Brain Surgeon (OBS) to achieve <b>SOTA</b> compression with high generative quality.
-      </p>
-    </td>
-  </tr>
-</table>
+<div style="
+    display: flex; 
+    flex-wrap: wrap; 
+    align-items: flex-start; 
+    gap: 20px; 
+    border: 1px solid #e0e0e0; 
+    padding: 20px; 
+    border-radius: 10px; 
+    margin-bottom: 20px; 
+    background-color: #fff;
+">
+  
+  <div style="flex: 1; min-width: 280px; max-width: 100%;">
+    <img src="teaser.jpg" alt="OBS-Diff" style="width: 100%; height: auto; border-radius: 5px;" />
+  </div>
+
+  <div style="flex: 2; min-width: 300px;">
+    <h4 style="margin-top: 0;">✂️ <a href="https://alrightlone.github.io/OBS-Diff-Webpage/">OBS-Diff: Accurate Pruning for Diffusion Models in One-Shot</a></h4>
+    <p>
+      <em><b>Junhan Zhu</b>, Hesong Wang, Mingluo Su, Zefang Wang, Huan Wang*</em>
+      <br>
+      <a href="https://arxiv.org/abs/2510.06751"><img src="https://img.shields.io/badge/Preprint-arXiv-b31b1b.svg?style=flat-square"></a>
+      <a href="https://github.com/Alrightlone/OBS-Diff"><img src="https://img.shields.io/github/stars/Alrightlone/OBS-Diff?style=flat-square&logo=github"></a>
+    </p>
+    <p>
+      The <b>first training-free, one-shot pruning framework</b> for Diffusion Models, supporting diverse architectures and pruning granularities. Uses Optimal Brain Surgeon (OBS) to achieve <b>SOTA</b> compression with high generative quality.
+    </p>
+  </div>
+
+</div></div>
 
 OBS-Diff-SDXL provides a collection of structured-pruned checkpoints for the Stable Diffusion XL (SDXL) base model, compressed using the OBS-Diff framework. By leveraging an efficient one-shot pruning algorithm, this model significantly reduces the parameter count of the UNet while maintaining high-fidelity image generation capabilities. The provided variants cover a sparsity range from 10% to 30%, offering a trade-off between model size and performance.
 ![](sdxl1.png)