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import gradio as gr
from gradio_leaderboard import Leaderboard
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
""")
Leaderboard(value=df,
allow_column_select=True,
on_load_columns=config.ON_LOAD_COLUMNS,
search_column="model_name_for_query",
hide_columns=["model_name_for_query", "Model Size"],
filter_columns=config.FILTER_COLUMNS,
datatype=config.TYPES,
column_widths=["2%", "33%"])
if __name__ == "__main__":
demo.launch()