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Running
on
CPU Upgrade
Running
on
CPU Upgrade
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() | |