change style

app.py

@@ -408,56 +408,60 @@ css = """
     width: 100% !important;
 }
 
-/* Quantize button styling with glow effect */
-button[variant="primary"] {
-    background: linear-gradient(135deg, #3B82F6, #10B981) !important;
-    color: white !important;
-    padding: 16px 32px !important;
-    font-size: 1.1rem !important;
-    font-weight: 700 !important;
-    border: none !important;
-    border-radius: 12px !important;
-    box-shadow: 0 0 15px rgba(59, 130, 246, 0.5) !important;
-    transition: all 0.3s cubic-bezier(0.25, 0.8, 0.25, 1) !important;
-    position: relative;
-    overflow: hidden;
-    animation: glow 1.5s ease-in-out infinite alternate;
-}
 
 button[variant="primary"]::before {
-    content: "✨ ";
+    content: "🔥 ";  /* PyTorch flame icon */
 }
 
 button[variant="primary"]:hover {
     transform: translateY(-5px) scale(1.05) !important;
-    box-shadow: 0 10px 25px rgba(59, 130, 246, 0.7) !important;
+    box-shadow: 0 10px 25px rgba(238, 76, 44, 0.7) !important;
 }
 
-@keyframes glow {
+@keyframes pytorch-glow {
     from {
-        box-shadow: 0 0 10px rgba(59, 130, 246, 0.5);
+        box-shadow: 0 0 10px rgba(238, 76, 44, 0.5);
     }
     to {
-        box-shadow: 0 0 20px rgba(59, 130, 246, 0.8), 0 0 30px rgba(16, 185, 129, 0.5);
+        box-shadow: 0 0 20px rgba(238, 76, 44, 0.8), 0 0 30px rgba(255, 156, 0, 0.5);
     }
 }
 
 /* Login button styling */
 #login-button {
-    background: linear-gradient(135deg, #3B82F6, #10B981) !important;
+    background: linear-gradient(135deg, #EE4C2C, #FF9C00) !important;
     color: white !important;
     font-weight: 700 !important;
     border: none !important;
-    border-radius: 12px !important;
-    box-shadow: 0 0 15px rgba(59, 130, 246, 0.5) !important;
+    border-radius: 15px !important;
+    box-shadow: 0 0 15px rgba(238, 76, 44, 0.5) !important;
     transition: all 0.3s ease !important;
     max-width: 300px !important;
     margin: 0 auto !important;
 }
+
+.quantize-button {
+    background: linear-gradient(135deg, #EE4C2C, #FF9C00) !important;
+    color: white !important;
+    font-weight: 700 !important;
+    border: none !important;
+    border-radius: 15px !important;
+    box-shadow: 0 0 15px rgba(238, 76, 44, 0.5) !important;
+    transition: all 0.3s ease !important;
+    animation: pytorch-glow 1.5s infinite alternate !important;
+    transform-origin: center !important;
+    letter-spacing: 0.5px !important;
+    text-shadow: 0 1px 2px rgba(0, 0, 0, 0.2) !important;
+}
+
+.quantize-button:hover {
+    transform: translateY(-3px) scale(1.03) !important;
+    box-shadow: 0 8px 20px rgba(238, 76, 44, 0.7) !important;
+}
 """
 
 # Update the main app layout
-with gr.Blocks(theme=gr.themes.Ocean(), css=css) as demo:
+with gr.Blocks(css=css) as demo:
     gr.Markdown(
         """
         # 🤗 TorchAO Model Quantizer ✨
@@ -532,7 +536,7 @@ with gr.Blocks(theme=gr.themes.Ocean(), css=css) as demo:
 
         with gr.Column():
             quantize_button = gr.Button(
-                "🚀 Quantize and Push to Hub", variant="primary"
+                "🚀 Quantize and Push to Hub", elem_classes="quantize-button", elem_id="quantize-button"
             )
             output_link = gr.Markdown(
                 label="🔗 Quantized Model Info", container=True, min_height=200
@@ -545,10 +549,13 @@ with gr.Blocks(theme=gr.themes.Ocean(), css=css) as demo:
             ## 📝 Quantization Options
             
             ### Quantization Types
-            - **int4_weight_only**: 4-bit weight-only quantization
+            - **int4_weight_only**: 4-bit weight-only quantization 
             - **int8_weight_only**: 8-bit weight-only quantization
             - **int8_dynamic_activation_int8_weight**: 8-bit quantization for both weights and activations
-            
+            - **float8_weight_only**: float8-bit weight-only quantization
+            - **float8_dynamic_activation_float8_weight**: float8-bit quantization for both weights and activations
+            - **autoquant**: automatic quantization (uses the best quantization method for the model)
+
             ### Group Size
             - Only applicable for int4_weight_only and int8_weight_only quantization
             - Default value is 128
@@ -560,8 +567,8 @@ with gr.Blocks(theme=gr.themes.Ocean(), css=css) as demo:
             3. Uploads the quantized model to your HuggingFace account
             
             ## 📊 Memory Benefits
-            - int4_weight_only can reduce model size by up to 75%
-            - int8_weight_only typically reduces size by about 50%
+            - int4 quantization can reduce model size by up to 75%
+            - int8 quantization typically reduces size by about 50%
             """
         )
     # Keep existing click handler