Update app.py

app.py

@@ -49,10 +49,10 @@ def get_plots(task):
     df['energy_score'] = df['energy_score'].astype(int).astype(str)
     # Create a display model column for labeling
     df['Display Model'] = df['model'].apply(lambda m: m.split('/')[-1])
-    
+
     # Use the energy score to control color
     color_map = {"1": "red", "2": "orange", "3": "yellow", "4": "lightgreen", "5": "green"}
-    
+
     # Now plot with the model name on the X axis and GPU Energy on the Y axis.
     fig = px.scatter(
         df,
@@ -74,7 +74,8 @@ def get_plots(task):
     )
     fig.update_layout(
         xaxis_title="Model",
-        yaxis_title="GPU Energy (Wh)"
+        yaxis_title="GPU Energy (Wh)",
+        yaxis_tickformat=".4f" # Add this line to format y-axis ticks
     )
     return fig
 
@@ -89,9 +90,9 @@ def get_all_plots():
         df['Display Model'] = df['model'].apply(lambda m: m.split('/')[-1])
         all_df = pd.concat([all_df, df], ignore_index=True)
     all_df = all_df.drop_duplicates(subset=['model'])
-    
+
     color_map = {"1": "red", "2": "orange", "3": "yellow", "4": "lightgreen", "5": "green"}
-    
+
     fig = px.scatter(
         all_df,
         x="Display Model",
@@ -111,7 +112,8 @@ def get_all_plots():
     )
     fig.update_layout(
         xaxis_title="Model",
-        yaxis_title="GPU Energy (Wh)"
+        yaxis_title="GPU Energy (Wh)",
+        yaxis_tickformat=".4f" # Add this line to format y-axis ticks
     )
     return fig
 
@@ -156,9 +158,9 @@ def get_text_generation_plots(model_class):
     df['total_gpu_energy'] = pd.to_numeric(df['total_gpu_energy'], errors='raise')
     df['energy_score'] = df['energy_score'].astype(int).astype(str)
     df['Display Model'] = df['model'].apply(lambda m: m.split('/')[-1])
-    
+
     color_map = {"1": "red", "2": "orange", "3": "yellow", "4": "lightgreen", "5": "green"}
-    
+
     fig = px.scatter(
         df,
         x="Display Model",
@@ -178,7 +180,8 @@ def get_text_generation_plots(model_class):
     )
     fig.update_layout(
         xaxis_title="Model",
-        yaxis_title="GPU Energy (Wh)"
+        yaxis_title="GPU Energy (Wh)",
+        yaxis_tickformat=".4f" # Add this line to format y-axis ticks
     )
     return fig
 
@@ -223,7 +226,7 @@ with demo:
 ### Welcome to the leaderboard for the [AI Energy Score Project!](https://huggingface.co/AIEnergyScore)
 Select different tasks to see scored models. Submit open models for testing and learn about testing proprietary models via the [submission portal](https://huggingface.co/spaces/AIEnergyScore/submission_portal)"""
     )
-    
+
     with gr.Tabs():
         # --- Text Generation Tab with Dropdown for Model Class ---
         with gr.TabItem("Text Generation 💬"):
@@ -240,77 +243,77 @@ Select different tasks to see scored models. Submit open models for testing and
             model_class_dropdown.change(fn=update_text_generation,
                                         inputs=model_class_dropdown,
                                         outputs=[tg_plot, tg_table])
-        
+
         with gr.TabItem("Image Generation 📷"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_plots('image_generation.csv'))
                 with gr.Column():
                     table = gr.Dataframe(get_model_names('image_generation.csv'), datatype="markdown")
-                    
+
         with gr.TabItem("Text Classification 🎭"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_plots('text_classification.csv'))
                 with gr.Column():
                     table = gr.Dataframe(get_model_names('text_classification.csv'), datatype="markdown")
-                    
+
         with gr.TabItem("Image Classification 🖼️"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_plots('image_classification.csv'))
                 with gr.Column():
                     table = gr.Dataframe(get_model_names('image_classification.csv'), datatype="markdown")
-                    
+
         with gr.TabItem("Image Captioning 📝"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_plots('image_captioning.csv'))
                 with gr.Column():
                     table = gr.Dataframe(get_model_names('image_captioning.csv'), datatype="markdown")
-                    
+
         with gr.TabItem("Summarization 📃"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_plots('summarization.csv'))
                 with gr.Column():
                     table = gr.Dataframe(get_model_names('summarization.csv'), datatype="markdown")
-                    
+
         with gr.TabItem("Automatic Speech Recognition 💬"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_plots('asr.csv'))
                 with gr.Column():
                     table = gr.Dataframe(get_model_names('asr.csv'), datatype="markdown")
-                    
+
         with gr.TabItem("Object Detection 🚘"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_plots('object_detection.csv'))
                 with gr.Column():
                     table = gr.Dataframe(get_model_names('object_detection.csv'), datatype="markdown")
-                    
+
         with gr.TabItem("Sentence Similarity 📚"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_plots('sentence_similarity.csv'))
                 with gr.Column():
                     table = gr.Dataframe(get_model_names('sentence_similarity.csv'), datatype="markdown")
-                    
+
         with gr.TabItem("Extractive QA ❔"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_plots('question_answering.csv'))
                 with gr.Column():
                     table = gr.Dataframe(get_model_names('question_answering.csv'), datatype="markdown")
-                    
+
         with gr.TabItem("All Tasks 💡"):
             with gr.Row():
                 with gr.Column():
                     plot = gr.Plot(get_all_plots())
                 with gr.Column():
                     table = gr.Dataframe(get_all_model_names(), datatype="markdown")
-                    
+
     with gr.Accordion("📙 Citation", open=False):
         citation_button = gr.Textbox(
             value=CITATION_BUTTON_TEXT,
@@ -323,4 +326,4 @@ Select different tasks to see scored models. Submit open models for testing and
         """Last updated: February 2025"""
     )
 
-demo.launch()
+demo.launch()