import gradio as gr from gradio_leaderboard import Leaderboard, SelectColumns import config from pathlib import Path import pandas as pd abs_path = Path(__file__).parent df = pd.read_json(str(abs_path / "leaderboard_data.json")) # Make a model size column numeric_interval = pd.IntervalIndex( sorted([config.NUMERIC_INTERVALS[s] for s in config.NUMERIC_INTERVALS.keys()]) ) params_column = pd.to_numeric(df["#Params (B)"], errors="coerce") df["Model Size"] = params_column.apply( lambda x: next(s for s in numeric_interval if x in s) ) with gr.Blocks() as demo: gr.Markdown(""" # 🥇 Leaderboard Component """) with gr.Tabs(): with gr.Tab("Demo"): Leaderboard( value=df, select_columns=SelectColumns( default_selection=config.ON_LOAD_COLUMNS, cant_deselect=["T", "Model"], label="Select Columns to Display:", ), search_columns=["model_name_for_query", "Type"], hide_columns=["model_name_for_query", "Model Size"], filter_columns=config.FILTER_COLUMNS, datatype=config.TYPES, ) with gr.Tab("Docs"): gr.Markdown((Path(__file__).parent / "docs.md").read_text()) if __name__ == "__main__": demo.launch()