import gradio as gr from gradio_leaderboard import Leaderboard, SelectColumns, ColumnFilter from pathlib import Path from utils import LLM_BENCHMARKS_ABOUT_TEXT, LLM_BENCHMARKS_SUBMIT_TEXT, custom_css, jsonl_to_dataframe, add_average_column_to_df, apply_markdown_format_for_columns, submit, PART_LOGO, sort_dataframe_by_column abs_path = Path(__file__).parent # Any pandas-compatible data leaderboard_df = jsonl_to_dataframe(str(abs_path / "leaderboard_data.jsonl")) average_column_name = "Average Accuracy" all_columns = ["Model", average_column_name, "Precision", "#Params (B)", "MMLU", "GSM8K", "TruthfulQA", "Winogrande", "ARC Easy", "Hellaswag", "Belebele"] columns_to_average = ["MMLU", "GSM8K", "TruthfulQA", "Winogrande", "ARC Easy", "Hellaswag", "Belebele"] leaderboard_df = add_average_column_to_df(leaderboard_df, columns_to_average, index=3, average_column_name=average_column_name) leaderboard_df = apply_markdown_format_for_columns(df=leaderboard_df, model_column_name="Model") leaderboard_df = sort_dataframe_by_column(leaderboard_df, column_name=average_column_name) columns_data_type = ["markdown" for i in range(len(leaderboard_df.columns))] # "str", "number", "bool", "date", "markdown" # columns_data_type[0] = "markdown" NUM_MODELS=len(leaderboard_df) with gr.Blocks(css=custom_css) as demo: gr.Markdown(""" # Open Lithuanian LLM Leaderboard """) gr.Markdown(f""" - **Total Models**: {NUM_MODELS} """) with gr.Tab("🎖️ Lithuanian Leaderboard"): Leaderboard( value=leaderboard_df, datatype=columns_data_type, select_columns=SelectColumns( default_selection=all_columns, cant_deselect=["Model"], label="Select Columns to Show", ), search_columns=["model_name_for_query"], hide_columns=["model_name_for_query",], filter_columns=["Precision", "#Params (B)"], ) with gr.TabItem("📝 About"): gr.Markdown(LLM_BENCHMARKS_ABOUT_TEXT) with gr.Tab("✉️ Submit"): gr.Markdown(LLM_BENCHMARKS_SUBMIT_TEXT) model_name = gr.Textbox(label="Model name") model_id = gr.Textbox(label="username/space e.g neurotechnology/Lt-Llama-2-7b-hf") 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=[]) gr.Markdown(""" Please find more information about Neurotechnology on [www.neurotechnology.com](https://www.neurotechnology.com/natural-language-processing.html)""") if __name__ == "__main__": demo.launch()