better description

app.py

@@ -51,30 +51,28 @@ def query_image(input_img, query, binarize, eval_threshold):
 
 # Gradio interface
 description = """
-<div class="body">
-    Gradio demo for an object detection architecture, introduced in my <a href="https://www.google.com/">bachelor thesis</a> (link will be added). 
-    \n\n
-    You can use this architecture to detect objects using textual queries. To use it, simply upload an image and enter any query you want.
-    It can be a single word or in the form of a sentence. The model is trained to recognize only 80 categories from the COCO Detection 2017 dataset. 
-    Refer to <a href="https://tech.amikelive.com/node-718/what-object-categories-labels-are-in-coco-dataset/">this</a> website 
-    or the original <a href="https://arxiv.org/pdf/1405.0312.pdf">COCO</a> paper to see the full list of categories.
-    \n\n
-    Best results are obtained using one of these sentences, which were used during training:
-    <div class="row">
-        <div class="column">
-            <ul>
-                <li>Find a {class}.</li>
-                <li>Tea</li>
-                <li>Milk</li>
-            </ul>
-        </div>
-        <div class="column">
-            <ul>
-                <li>Coffee</li>
-                <li>Tea</li>
-                <li>Milk</li>
-            </ul>
-        </div>
+Gradio demo for an object detection architecture, introduced in my <a href="https://www.google.com/">bachelor thesis</a> (link will be added). 
+\n\n
+You can use this architecture to detect objects using textual queries. To use it, simply upload an image and enter any query you want.
+It can be a single word or in the form of a sentence. The model is trained to recognize only 80 categories from the COCO Detection 2017 dataset. 
+Refer to <a href="https://tech.amikelive.com/node-718/what-object-categories-labels-are-in-coco-dataset/">this</a> website 
+or the original <a href="https://arxiv.org/pdf/1405.0312.pdf">COCO</a> paper to see the full list of categories.
+\n\n
+Best results are obtained using one of these sentences, which were used during training:
+<div class="row">
+    <div class="column">
+        <ul>
+            <li>Find a {class}.</li>
+            <li>Tea</li>
+            <li>Milk</li>
+        </ul>
+    </div>
+    <div class="column">
+        <ul>
+            <li>Coffee</li>
+            <li>Tea</li>
+            <li>Milk</li>
+        </ul>
     </div>
 </div>
 """
@@ -93,9 +91,6 @@ demo = gr.Interface(
     cache_examples=False,
     allow_flagging = "never",
     css = """
-    .body {
-      font-size: 14px;
-    }
     .row {
       display: flex;
     }