Update app.py

app.py

@@ -51,7 +51,7 @@ def plot_average_scores():
     df_full["Average Score"] = df_full.iloc[:, 2:].mean(axis=1)
     df_avg_sorted = df_full.sort_values(by="Average Score", ascending=False)
 
-    plt.figure(figsize=(12, 8))
+    plt.figure(figsize=(14, 10))
     plt.barh(df_avg_sorted["Model Configuration"], df_avg_sorted["Average Score"])
     plt.title("Average Performance of Models Across Tasks", fontsize=16)
     plt.xlabel("Average Score", fontsize=14)
@@ -75,7 +75,7 @@ def plot_average_scores():
 def plot_task_performance():
     df_full_melted = df_full.melt(id_vars=["Model Configuration", "Model Link"], var_name="Task", value_name="Score")
 
-    plt.figure(figsize=(14, 10))
+    plt.figure(figsize=(16, 12))
     for model in df_full["Model Configuration"]:
         model_data = df_full_melted[df_full_melted["Model Configuration"] == model]
         plt.plot(model_data["Task"], model_data["Score"], marker="o", label=model)
@@ -105,7 +105,7 @@ def plot_task_specific_top_models():
 
     results = pd.DataFrame({"Top Model": top_models, "Score": top_scores}).reset_index().rename(columns={"index": "Task"})
 
-    plt.figure(figsize=(12, 6))
+    plt.figure(figsize=(14, 8))
     plt.bar(results["Task"], results["Score"])
     plt.title("Task-Specific Top Models", fontsize=16)
     plt.xlabel("Task", fontsize=14)
@@ -139,7 +139,7 @@ def scrape_mergekit_config(model_name):
     return f"No YAML configuration found for {model_name}."
 
 def plot_heatmap():
-    plt.figure(figsize=(12, 8))
+    plt.figure(figsize=(14, 10))
     sns.heatmap(df_full.iloc[:, 2:], annot=True, cmap="YlGnBu", xticklabels=columns[2:], yticklabels=df_full["Model Configuration"])
     plt.title("Performance Heatmap", fontsize=16)
     plt.tight_layout()
@@ -240,40 +240,28 @@ with gr.Blocks() as demo:
     gr.Markdown("# Comprehensive Model Performance Analysis with Hugging Face Links")
 
     with gr.Row():
-        with gr.Column(width=3):
-          btn1 = gr.Button("Show Average Performance")
-        with gr.Column(width=7):
-          img1 = gr.Image(type="pil", label="Average Performance Plot")
-        with gr.Column(width=2):
-          img1_download = gr.File(label="Download Average Performance")
+        btn1 = gr.Button("Show Average Performance")
+        img1 = gr.Image(type="pil", label="Average Performance Plot")
+        img1_download = gr.File(label="Download Average Performance")
         btn1.click(plot_average_scores, outputs=[img1,img1_download])
         
     with gr.Row():
-        with gr.Column(width=3):
-            btn2 = gr.Button("Show Task Performance")
-        with gr.Column(width=7):
-            img2 = gr.Image(type="pil", label="Task Performance Plot")
-        with gr.Column(width=2):
-            img2_download = gr.File(label="Download Task Performance")
+        btn2 = gr.Button("Show Task Performance")
+        img2 = gr.Image(type="pil", label="Task Performance Plot")
+        img2_download = gr.File(label="Download Task Performance")
         btn2.click(plot_task_performance, outputs=[img2, img2_download])
 
     with gr.Row():
-        with gr.Column(width=3):
-            btn3 = gr.Button("Task-Specific Top Models")
-        with gr.Column(width=7):
-            img3 = gr.Image(type="pil", label="Task-Specific Top Models Plot")
-        with gr.Column(width=2):
-            img3_download = gr.File(label="Download Top Models")
+        btn3 = gr.Button("Task-Specific Top Models")
+        img3 = gr.Image(type="pil", label="Task-Specific Top Models Plot")
+        img3_download = gr.File(label="Download Top Models")
         btn3.click(plot_task_specific_top_models, outputs=[img3, img3_download])
     
     with gr.Row():
-        with gr.Column(width=3):
-            btn4 = gr.Button("Plot Performance Heatmap")
-        with gr.Column(width=7):
-            heatmap_img = gr.Image(type="pil", label="Performance Heatmap")
-        with gr.Column(width=2):
-            heatmap_download = gr.File(label="Download Heatmap")
-        btn4.click(plot_heatmap, outputs=[heatmap_img, heatmap_download])
+      btn4 = gr.Button("Plot Performance Heatmap")
+      heatmap_img = gr.Image(type="pil", label="Performance Heatmap")
+      heatmap_download = gr.File(label="Download Heatmap")
+      btn4.click(plot_heatmap, outputs=[heatmap_img, heatmap_download])
 
     with gr.Row():
         model_selector = gr.Dropdown(choices=df_full["Model Configuration"].tolist(), label="Select a Model")