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import gradio as gr |
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from gradio_leaderboard import Leaderboard, SelectColumns, ColumnFilter |
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import config |
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from pathlib import Path |
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import pandas as pd |
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import random |
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abs_path = Path(__file__).parent |
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df = pd.read_json(str(abs_path / "leaderboard_data.json")) |
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df["MOE"] = [random.random() > 0.5 for _ in range(len(df))] |
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df["Flagged"] = [random.random() > 0.5 for _ in range(len(df))] |
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with gr.Blocks() as demo: |
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gr.Markdown(""" |
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# 🥇 Leaderboard Component |
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""") |
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with gr.Tabs(): |
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with gr.Tab("Demo"): |
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Leaderboard( |
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value=df, |
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select_columns=SelectColumns( |
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default_selection=config.ON_LOAD_COLUMNS, |
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cant_deselect=["T", "Model"], |
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label="Select Columns to Display:", |
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), |
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search_columns=["model_name_for_query", "Type"], |
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hide_columns=["model_name_for_query", "Model Size"], |
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filter_columns=[ |
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"T", |
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"Precision", |
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ColumnFilter("MOE", type="boolean", default=False, label="MoE"), |
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ColumnFilter("Flagged", type="boolean", default=False), |
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ColumnFilter("#Params (B)", default=[30, 80]), |
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], |
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datatype=config.TYPES, |
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column_widths=["2%", "33%"], |
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) |
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with gr.Tab("Docs"): |
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gr.Markdown((Path(__file__).parent / "docs.md").read_text()) |
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if __name__ == "__main__": |
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demo.launch() |
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