Update README.md

README.md

@@ -66,26 +66,26 @@ output = cf(**{'input_text': input_text, 'image/encoded': image_encoded})
 
 <table style="width:100%; border-collapse: collapse; font-family: Arial, sans-serif;">
     <tr>
-        <th style="width: 30%; border: 1px solid #333; padding: 10px; background-color: #f2f2f2;">Model Architecture</th>
+        <th style="width: 30%; border: 1px solid #333; padding: 10px;">Model Architecture</th>
         <td style="border: 1px solid #333; padding: 10px;">A multimodal sequence-to-sequence Transformer model with the mT5 encoder-decoder architecture. It takes text tokens and ViT dense image embeddings as inputs to an encoder and autoregressively predicts discrete text and ink tokens with a decoder.</td>
     </tr>
     <tr>
-        <th style="width: 30%; border: 1px solid #333; padding: 10px; background-color: #f2f2f2;">Input(s)</th>
+        <th style="width: 30%; border: 1px solid #333; padding: 10px;">Input(s)</th>
         <td style="border: 1px solid #333; padding: 10px;">A pair of image and text.</td>
     </tr>
     <tr>
-        <th style="width: 30%; border: 1px solid #333; padding: 10px; background-color: #f2f2f2;">Output(s)</th>
+        <th style="width: 30%; border: 1px solid #333; padding: 10px;">Output(s)</th>
         <td style="border: 1px solid #333; padding: 10px;">Generated digital ink and text.</td>
     </tr>
     <tr>
-        <th style="width: 30%; border: 1px solid #333; padding: 10px; background-color: #f2f2f2;">Usage</th>
+        <th style="width: 30%; border: 1px solid #333; padding: 10px;">Usage</th>
         <td style="border: 1px solid #333; padding: 10px;">
             <strong>Application:</strong> The model is for research prototype, and the public version is released and available for the public.<br>
             <strong>Known Caveats:</strong> None.
         </td>
     </tr>
     <tr>
-        <th style="width: 30%; border: 1px solid #333; padding: 10px; background-color: #f2f2f2;">System Type</th>
+        <th style="width: 30%; border: 1px solid #333; padding: 10px;">System Type</th>
         <td style="border: 1px solid #333; padding: 10px;">
             <strong>System Description:</strong> This is a standalone model.<br>
             <strong>Upstream Dependencies:</strong> None.<br>
@@ -93,7 +93,7 @@ output = cf(**{'input_text': input_text, 'image/encoded': image_encoded})
         </td>
     </tr>
     <tr>
-        <th style="width: 30%; border: 1px solid #333; padding: 10px; background-color: #f2f2f2;">Implementation Frameworks</th>
+        <th style="width: 30%; border: 1px solid #333; padding: 10px;">Implementation Frameworks</th>
         <td style="border: 1px solid #333; padding: 10px;">
             <strong>Hardware & Software:</strong> Hardware: TPU v5e.<br>
             Software: T5X , JAX/Flax, Flaxformer.<br>
@@ -101,19 +101,19 @@ output = cf(**{'input_text': input_text, 'image/encoded': image_encoded})
         </td>
     </tr>
     <tr>
-        <th style="width: 30%; border: 1px solid #333; padding: 10px; background-color: #f2f2f2;">Data Overview</th>
+        <th style="width: 30%; border: 1px solid #333; padding: 10px;">Data Overview</th>
         <td style="border: 1px solid #333; padding: 10px;">
             <strong>Training Datasets:</strong> The ViT encoder of Small-p is pretrained on ImageNet-21k, mT5 encoder and decoder are initialized from scratch. The entire model is trained on the mixture of publicly available datasets described in next section.
         </td>
     </tr>
     <tr>
-        <th style="width: 30%; border: 1px solid #333; padding: 10px; background-color: #f2f2f2;">Evaluation Results</th>
+        <th style="width: 30%; border: 1px solid #333; padding: 10px;">Evaluation Results</th>
         <td style="border: 1px solid #333; padding: 10px;">
             <strong>Evaluation Methods:</strong> Human evaluation (reported in Section 4.5.1 of the paper) and automated evaluations (reported in Section 4.5.2 of the paper).
         </td>
     </tr>
     <tr>
-        <th style="width: 30%; border: 1px solid #333; padding: 10px; background-color: #f2f2f2;">Model Usage & Limitations</th>
+        <th style="width: 30%; border: 1px solid #333; padding: 10px;">Model Usage & Limitations</th>
         <td style="border: 1px solid #333; padding: 10px;">
             <strong>Sensitive Use:</strong> The model is capable of converting images to digital inks. This model should not be used for any of the privacy-intruding use cases, e.g., forging handwritings.<br>
             <strong>Known Limitations:</strong> Reported in Appendix I of the paper.<br>
@@ -122,7 +122,6 @@ output = cf(**{'input_text': input_text, 'image/encoded': image_encoded})
     </tr>
 </table>
 
-
 ## Citation
 
 If you find our work useful for your research and applications, please cite using this BibTeX: