|
|
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_clickable_model, submit |
|
|
|
|
|
|
|
|
|
|
|
abs_path = Path(__file__).parent |
|
|
|
|
|
|
|
|
persian_df = jsonl_to_dataframe(str(abs_path / "leaderboard_persian.jsonl")) |
|
|
base_df = jsonl_to_dataframe(str(abs_path / "leaderboard_base.jsonl")) |
|
|
|
|
|
|
|
|
all_columns = ["Model", "Average ⬆️", "Precision", "#Params (B)", "Part Multiple Choice", "ARC Easy", "ARC Challenging", "MMLU Pro", "GSM8k Persian", "Multiple Choice Persian"] |
|
|
columns_to_average = ["Part Multiple Choice", "ARC Easy", "ARC Challenging", "MMLU Pro", "GSM8k Persian", "Multiple Choice Persian"] |
|
|
|
|
|
|
|
|
base_df = add_average_column_to_df(base_df, columns_to_average, index=3) |
|
|
persian_df = add_average_column_to_df(persian_df, columns_to_average, index=3) |
|
|
|
|
|
base_df = apply_clickable_model(df=base_df, column_name="Model") |
|
|
persian_df = apply_clickable_model(df=persian_df, column_name="Model") |
|
|
|
|
|
columns_data_type = ["str" for i in range(len(persian_df.columns))] |
|
|
|
|
|
|
|
|
columns_data_type[0] = "markdown" |
|
|
|
|
|
with gr.Blocks(css=custom_css) as demo: |
|
|
gr.Markdown(""" |
|
|
# Part LLM Leaderboard |
|
|
""") |
|
|
|
|
|
with gr.Tab("🎖️ Persian Leaderboard"): |
|
|
gr.Markdown("""## Persian LLM Leaderboard |
|
|
Evaluating Persian Fine-Tuned models |
|
|
""") |
|
|
Leaderboard( |
|
|
value=persian_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.Tab("🥇 Base Leaderboard"): |
|
|
gr.Markdown("""## Base LLM Leaderboard |
|
|
Evaluating Base Models |
|
|
""") |
|
|
Leaderboard( |
|
|
value=base_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 mlsb/alphafold3") |
|
|
contact_email = gr.Textbox(label="Contact E-Mail") |
|
|
challenge = gr.Radio(choices=["Persian", "Base"],label="Challenge") |
|
|
gr.Markdown("Either give a submission id if you submitted to the MLSB workshop or provide a link to the preprint/paper describing the method.") |
|
|
with gr.Row(): |
|
|
submission_id = gr.Textbox(label="Submission ID on CMT") |
|
|
paper_link = gr.Textbox(label="Preprint or Paper link") |
|
|
architecture = gr.Dropdown(choices=["GNN", "CNN","Diffusion Model", "Physics-based", "Other"],label="Model architecture") |
|
|
license = gr.Dropdown(choices=["mit", "apache-2.0", "gplv2", "gplv3", "lgpl", "mozilla", "bsd", "other"],label="License") |
|
|
submit_btn = gr.Button("Submit") |
|
|
|
|
|
submit_btn.click(submit, inputs=[model_name, model_id, contact_email, challenge, submission_id, paper_link, architecture, license], outputs=[]) |
|
|
|
|
|
gr.Markdown(""" |
|
|
Please find more information about the challenges on [mlsb.io/#challenge](https://mlsb.io/#challenge)""") |
|
|
|
|
|
if __name__ == "__main__": |
|
|
demo.launch() |
|
|
|
