Update app.py

app.py

@@ -173,13 +173,23 @@ def generate_shakespeare_outputs(prompt=None, max_new_tokens=2000):
 
 
 
-
-title = "Nano GPT"
-
-description1 = "Nano GPT trained on <a href='https://www.kaggle.com/datasets/mikeortman/wikipedia-sentences'>Shakespeare dataset</a>. It is trained on a very small amount of data to understand how GPT's are trained and built. The implementation can be found <a href='https://github.com/karpathy/nanoGPT'>here.</a>"
+icon_html = '<i class="fas fa-chart-bar"></i>'
+title = f"""
+<div style="background-color: #f5f1f2; padding: 10px; display: flex; align-items: center;">
+    {icon_html} <span style="margin-left: 10px;">Nano GPT</span>
+</div>
+"""
+description = f"""
+<div style="background-color: #f1f1f5; padding: 10px; display: flex; align-items: center;">
+    {icon_html}
+    <span style="margin-left: 10px;">
+        <p><strong>Nano GPT trained on <a href='https://www.kaggle.com/datasets/mikeortman/wikipedia-sentences'>Shakespeare dataset</a>. It is trained on a very small amount of data to understand how GPT's are trained and built. The implementation can be found <a href='https://github.com/karpathy/nanoGPT'>here.</a>"</strong></p>
+    </span>
+</div>
+"""
 
 shakespeare_interface = gr.Interface(generate_shakespeare_outputs,
-                    inputs=[gr.Textbox(label="Enter any prompt ", type="text", value="Once upon a time,"),
+                    inputs=[gr.Textbox(label="Enter any prompt ", type="text", value="Romeo"),
                             gr.Slider(minimum=100, maximum=5000, step=100, value=2000, label="Max new tokens")],
                     outputs=gr.Textbox(label="Output generated", type="text"), description=description1)