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Update app.py
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app.py
CHANGED
@@ -63,13 +63,11 @@ def generate_html_table_from_df(df):
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max_length = max(len(extract_link_text(link)) for link in df['Model'])
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else:
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max_length = 10
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# Multiply by an estimated average character width (10 pixels) and add some extra padding.
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static_width = max_length * 10 + 16
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max_energy = df['gpu_energy_numeric'].max() if not df.empty else 1
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color_map = {"1": "black", "2": "black", "3": "black", "4": "black", "5": "black"}
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html = '<table style="width:100%; border-collapse: collapse; font-family: Inter, sans-serif;">'
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# Keep only one header (the one with hover text)
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html += '<thead><tr style="background-color: #f2f2f2;">'
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html += '<th style="text-align: left; padding: 8px;" title="Model name with link to Hugging Face">Model</th>'
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html += '<th style="text-align: left; padding: 8px;" title="GPU energy consumed in Watt-hours for 1,000 queries">GPU Energy (Wh)</th>'
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@@ -79,7 +77,6 @@ def generate_html_table_from_df(df):
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for _, row in df.iterrows():
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energy_numeric = row['gpu_energy_numeric']
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energy_str = f"{energy_numeric:.2f}"
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# Compute the relative width (as a percentage)
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bar_width = (energy_numeric / max_energy) * 100
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score_val = row['energy_score']
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bar_color = color_map.get(str(score_val), "gray")
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@@ -92,7 +89,8 @@ def generate_html_table_from_df(df):
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html += f'<td style="padding: 8px;">{row["Score"]}</td>'
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html += '</tr>'
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html += '</tbody></table>'
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# --- Function to zip all CSV files ---
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def zip_csv_files():
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@@ -114,7 +112,7 @@ def get_zip_data_link():
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href = (
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f'<a href="data:application/zip;base64,{b64}" '
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'download="data.zip" '
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'style="
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'color: black; font-family: \'Inter\', sans-serif;">Download Data</a>'
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)
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return href
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@@ -125,7 +123,6 @@ def get_model_names_html(task, sort_order="Low to High"):
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if df.columns[0].startswith("Unnamed:"):
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df = df.iloc[:, 1:]
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df['energy_score'] = df['energy_score'].astype(int)
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# Convert kWh to Wh:
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df['gpu_energy_numeric'] = pd.to_numeric(df['total_gpu_energy'], errors='raise') * 1000
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df['Model'] = df['model'].apply(make_link)
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df['Score'] = df['energy_score'].apply(format_stars)
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@@ -164,8 +161,6 @@ def get_text_generation_model_names_html(model_class, sort_order="Low to High"):
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return generate_html_table_from_df(df)
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# --- Update functions for dropdown changes ---
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# For Text Generation, two dropdowns: model class and sort order.
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def update_text_generation(selected_display, sort_order):
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mapping = {
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"A (Single Consumer GPU) <20B parameters": "A",
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@@ -175,7 +170,6 @@ def update_text_generation(selected_display, sort_order):
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model_class = mapping.get(selected_display, "A")
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return get_text_generation_model_names_html(model_class, sort_order)
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# For the other tabs, each update function simply takes the sort_order.
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def update_image_generation(sort_order):
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return get_model_names_html('image_generation.csv', sort_order)
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@@ -207,7 +201,6 @@ def update_all_tasks(sort_order):
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return get_all_model_names_html(sort_order)
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# --- Build the Gradio Interface ---
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demo = gr.Blocks(css="""
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.gr-dataframe table {
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table-layout: fixed;
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@@ -219,49 +212,37 @@ demo = gr.Blocks(css="""
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overflow: hidden;
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text-overflow: ellipsis;
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}
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""")
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with demo:
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# --- Header Links (at the very top) ---
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faq_link = gr.HTML(
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'<a href="https://huggingface.github.io/AIEnergyScore/#faq" '
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'style="margin: 0 10px; text-decoration: none; font-weight: bold; font-size: 1.1em; '
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'color: black; font-family: \'Inter\', sans-serif;">FAQ</a>'
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)
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documentation_link = gr.HTML(
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'<a href="https://huggingface.github.io/AIEnergyScore/#documentation" '
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'style="margin: 0 10px; text-decoration: none; font-weight: bold; font-size: 1.1em; '
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'color: black; font-family: \'Inter\', sans-serif;">Documentation</a>'
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)
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download_link = gr.HTML(get_zip_data_link())
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community_link = gr.HTML(
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'<a href="https://huggingface.co/spaces/AIEnergyScore/README/discussions" '
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'style="margin: 0 10px; text-decoration: none; font-weight: bold; font-size: 1.1em; '
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'color: black; font-family: \'Inter\', sans-serif;">Community</a>'
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)
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# --- Logo (centered) ---
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gr.HTML('''
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<div style="
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<img src="https://huggingface.co/spaces/AIEnergyScore/Leaderboard/resolve/main/logo.png"
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alt="Logo"
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style="max-width: 300px; height: auto;">
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</div>
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''')
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# --- Subtitle (centered) ---
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gr.Markdown('<
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# --- Tabs for the different tasks ---
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with gr.Tabs():
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@@ -284,7 +265,6 @@ with demo:
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value="Low to High"
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)
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tg_table = gr.HTML(get_text_generation_model_names_html("A", "Low to High"))
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# When either dropdown changes, update the table.
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model_class_dropdown.change(fn=update_text_generation, inputs=[model_class_dropdown, sort_dropdown_tg], outputs=tg_table)
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sort_dropdown_tg.change(fn=update_text_generation, inputs=[model_class_dropdown, sort_dropdown_tg], outputs=tg_table)
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@@ -396,6 +376,6 @@ with demo:
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lines=10,
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show_copy_button=True,
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)
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gr.Markdown("
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demo.launch()
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max_length = max(len(extract_link_text(link)) for link in df['Model'])
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else:
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max_length = 10
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static_width = max_length * 10 + 16
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max_energy = df['gpu_energy_numeric'].max() if not df.empty else 1
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color_map = {"1": "black", "2": "black", "3": "black", "4": "black", "5": "black"}
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html = '<table style="width:100%; border-collapse: collapse; font-family: Inter, sans-serif;">'
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html += '<thead><tr style="background-color: #f2f2f2;">'
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html += '<th style="text-align: left; padding: 8px;" title="Model name with link to Hugging Face">Model</th>'
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html += '<th style="text-align: left; padding: 8px;" title="GPU energy consumed in Watt-hours for 1,000 queries">GPU Energy (Wh)</th>'
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for _, row in df.iterrows():
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energy_numeric = row['gpu_energy_numeric']
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energy_str = f"{energy_numeric:.2f}"
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bar_width = (energy_numeric / max_energy) * 100
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score_val = row['energy_score']
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bar_color = color_map.get(str(score_val), "gray")
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html += f'<td style="padding: 8px;">{row["Score"]}</td>'
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html += '</tr>'
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html += '</tbody></table>'
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# Wrap the table in a container so its edges match the dropdown menus.
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return f'<div class="table-container">{html}</div>'
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# --- Function to zip all CSV files ---
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def zip_csv_files():
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href = (
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f'<a href="data:application/zip;base64,{b64}" '
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'download="data.zip" '
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'style="text-decoration: none; font-weight: bold; font-size: 1.1em; '
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'color: black; font-family: \'Inter\', sans-serif;">Download Data</a>'
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)
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return href
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if df.columns[0].startswith("Unnamed:"):
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df = df.iloc[:, 1:]
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df['energy_score'] = df['energy_score'].astype(int)
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df['gpu_energy_numeric'] = pd.to_numeric(df['total_gpu_energy'], errors='raise') * 1000
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df['Model'] = df['model'].apply(make_link)
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df['Score'] = df['energy_score'].apply(format_stars)
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return generate_html_table_from_df(df)
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# --- Update functions for dropdown changes ---
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def update_text_generation(selected_display, sort_order):
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mapping = {
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"A (Single Consumer GPU) <20B parameters": "A",
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model_class = mapping.get(selected_display, "A")
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return get_text_generation_model_names_html(model_class, sort_order)
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def update_image_generation(sort_order):
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return get_model_names_html('image_generation.csv', sort_order)
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return get_all_model_names_html(sort_order)
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# --- Build the Gradio Interface ---
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demo = gr.Blocks(css="""
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.gr-dataframe table {
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table-layout: fixed;
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overflow: hidden;
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text-overflow: ellipsis;
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}
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.table-container {
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max-width: 800px;
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margin-left: auto;
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margin-right: auto;
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}
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""")
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with demo:
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# --- Header Links (at the very top, evenly spaced) ---
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gr.HTML(f'''
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<div style="display: flex; justify-content: space-evenly; align-items: center; margin-bottom: 20px;">
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<a href="https://huggingface.co/spaces/AIEnergyScore/submission_portal" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Submission Portal</a>
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<a href="https://huggingface.co/spaces/AIEnergyScore/Label" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Label Generator</a>
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<a href="https://huggingface.github.io/AIEnergyScore/#faq" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">FAQ</a>
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<a href="https://huggingface.github.io/AIEnergyScore/#documentation" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Documentation</a>
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{get_zip_data_link()}
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<a href="https://huggingface.co/spaces/AIEnergyScore/README/discussions" style="text-decoration: none; font-weight: bold; font-size: 1.1em; color: black; font-family: 'Inter', sans-serif;">Community</a>
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</div>
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''')
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# --- Logo (centered) ---
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gr.HTML('''
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<div style="margin-top: 20px;">
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<img src="https://huggingface.co/spaces/AIEnergyScore/Leaderboard/resolve/main/logo.png"
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alt="Logo"
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style="display: block; margin: 0 auto; max-width: 300px; height: auto;">
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</div>
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''')
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# --- Subtitle (centered) ---
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gr.Markdown('<div style="text-align: center;">Welcome to the AI Energy Score leaderboard. Select different tasks to see scored models.</div>')
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# --- Tabs for the different tasks ---
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with gr.Tabs():
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value="Low to High"
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)
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tg_table = gr.HTML(get_text_generation_model_names_html("A", "Low to High"))
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model_class_dropdown.change(fn=update_text_generation, inputs=[model_class_dropdown, sort_dropdown_tg], outputs=tg_table)
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sort_dropdown_tg.change(fn=update_text_generation, inputs=[model_class_dropdown, sort_dropdown_tg], outputs=tg_table)
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lines=10,
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show_copy_button=True,
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)
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gr.Markdown("Last updated: February 2025")
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demo.launch()
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