Update app.py

app.py

@@ -144,7 +144,6 @@ def evaluate_predictions(prediction_file, model_name, add_to_leaderboard):
 
 initialize_leaderboard_file()
 
-
 # Function to set default mode
 css_tech_theme = """
 body {
@@ -186,6 +185,19 @@ button:hover {
     box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
 }
 
+.tabs {
+    margin-bottom: 15px;
+    gap: 10px;
+}
+
+.tab-item {
+    background-color: #ece2f4;
+    border-radius: 6px;
+    padding: 10px;
+    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
+    margin: 5px;
+}
+
 .dataframe {
     color: #333333;
     background-color: #ffffff;
@@ -202,17 +214,17 @@ with gr.Blocks(css=css_tech_theme) as demo:
     gr.Markdown("""
 # 🏆 Mobile-MMLU Benchmark Competition
 ### 🌟 Welcome to the Competition Overview
-![Competition Logo](mobile_mmlu_sd.jpeg)
+![Competition Logo](https://via.placeholder.com/150)
 ---
-Welcome to the Mobile-MMLU Benchmark Competition. Here you can submit your predictions, view the leaderboard, and track your performance.
+Welcome to the **Mobile-MMLU Benchmark Competition**. Here you can submit your predictions, view the leaderboard, and track your performance.
 ---
     """)
 
-    with gr.Tabs():
-        with gr.TabItem("📖 Overview"):
+    with gr.Tabs(elem_id="tabs"):
+        with gr.TabItem("📖 Overview", elem_classes=["tab-item"]):
             gr.Markdown("""
 ## Overview
-Welcome to the Mobile-MMLU Benchmark Competition! Evaluate mobile-compatible Large Language Models (LLMs) on **16,186 scenario-based and factual questions** across **80 fields**.
+Welcome to the **Mobile-MMLU Benchmark Competition**! Evaluate mobile-compatible Large Language Models (LLMs) on **16,186 scenario-based and factual questions** across **80 fields**.
 ---
 ### What is Mobile-MMLU?
 Mobile-MMLU is a benchmark designed to test the capabilities of LLMs optimized for mobile use. Contribute to advancing mobile AI systems by competing to achieve the highest accuracy.
@@ -245,7 +257,7 @@ For support, email: [Insert Email Address]
 ---
             """)
 
-        with gr.TabItem("📤 Submission"):
+        with gr.TabItem("📤 Submission", elem_classes=["tab-item"]):
             with gr.Row():
                 file_input = gr.File(label="📂 Upload Prediction CSV", file_types=[".csv"], interactive=True)
                 model_name_input = gr.Textbox(label="🖋️ Model Name", placeholder="Enter your model name")
@@ -263,7 +275,7 @@ For support, email: [Insert Email Address]
                 outputs=[eval_status, overall_accuracy_display],
             )
 
-        with gr.TabItem("🏅 Leaderboard"):
+        with gr.TabItem("🏅 Leaderboard", elem_classes=["tab-item"]):
             leaderboard_table = gr.Dataframe(
                 value=load_leaderboard(),
                 label="Leaderboard",
@@ -280,5 +292,3 @@ For support, email: [Insert Email Address]
     gr.Markdown(f"**Last updated:** {LAST_UPDATED}")
 
 demo.launch()
-
-