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dae933d d220025 dae933d d220025 dae933d d220025 dae933d d220025 dae933d d220025 dae933d d220025 dae933d d220025 dae933d d220025 dae933d d220025 dae933d d220025 dae933d b4c2edd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | import gradio as gr
from gradio_leaderboard import Leaderboard, SelectColumns
from utils import (
LLM_BENCHMARKS_ABOUT_TEXT,
LLM_BENCHMARKS_SUBMIT_TEXT,
custom_css,
prepare_leaderboard_data,
submit
)
# Dataset Variables
overall_score_column = "overall"
model_name_column = "model"
precision_column = "precision"
num_params_column = "#parameters (B)"
# Prepare the data
leaderboard_df = prepare_leaderboard_data(overall_score_column, model_name_column)
# Determine columns data type (markdown for all to support clickable links)
columns_datatype = ["markdown" for _ in range(len(leaderboard_df.columns))]
NUM_MODELS = len(leaderboard_df)
with gr.Blocks(
css=custom_css,
theme=gr.themes.Default(
font=["sans-serif", "ui-sans-serif", "system-ui"],
font_mono=["monospace", "ui-monospace", "Consolas"]
)
) as demo:
gr.Markdown("""
# π CRCIS LLM Leaderboard
""")
gr.Markdown(f"""
- **Total Models**: {NUM_MODELS}
""")
with gr.Tab("π Leaderboard"):
Leaderboard(
value=leaderboard_df,
datatype=columns_datatype,
select_columns=SelectColumns(
default_selection=leaderboard_df.columns.tolist(),
cant_deselect=[model_name_column],
label="Select Columns to Show",
),
search_columns=[model_name_column],
filter_columns=[precision_column, num_params_column],
)
with gr.TabItem("π About"):
gr.Markdown(LLM_BENCHMARKS_ABOUT_TEXT)
with gr.Tab("π€ Submit"):
gr.Markdown(LLM_BENCHMARKS_SUBMIT_TEXT)
model_name = gr.Textbox(label="Model name")
model_id = gr.Textbox(label="Model ID (e.g., username/model-name)")
contact_email = gr.Textbox(label="Contact E-Mail")
submit_btn = gr.Button("Submit")
submit_btn.click(submit, inputs=[model_name, model_id, contact_email], outputs=[])
if __name__ == "__main__":
demo.launch() |