import gradio as gr import pandas as pd from create_table import create # 테이블 업데이트 def refresh(): table1, table2, table3 = create() return table1, table2, table3 with gr.Blocks() as demo: # 테이블 초기화 table1, table2, table3 = create() with gr.Row(): gr.Markdown( """ # 🏆 Iris Translation Leaderboard Iris Translation is a project designed to evaluate Korean-to-English translation models ## github - https://github.com/davidkim205/translation ## How to add model If you want to add a new model, please write the model name and template in the [github issue](https://github.com/davidkim205/translation/issues). ## evaluation criteria - **Bleu**: average bleu score - **SBleu**: Self-Bleu(double translation evaluation) - **Bleu-SL**: bleu by sentence length - **Duplicate**: count of repetitive sentence generation - **Length Exceeds**: count of mismatches in translated sentence lengths exceeding the threshold """ ) with gr.Row(): with gr.Tab("bleu and sbleu"): with gr.Group(): table1 = gr.Dataframe(value=table1, datatype="html") with gr.Accordion("Show Chart", open=False): gr.Image( "assets/plot-bleu.png", show_download_button=False, container=False, ) with gr.Tab("bleu by src"): with gr.Group(): table2 = gr.Dataframe(value=table2, datatype="html") with gr.Accordion("Show Chart", open=False): gr.Image( "assets/plot-bleu-by-src.png", show_download_button=False, container=False, ) with gr.Tab("bleu by sentence length"): with gr.Group(): table3 = gr.Dataframe(value=table3, datatype="html") with gr.Accordion("Show Chart", open=False): gr.Image( "assets/plot-bleu-by-sentence-length.png", show_download_button=False, container=False, ) refresh_btn = gr.Button(value="Refresh") refresh_btn.click(refresh, outputs=[table1, table2, table3]) demo.launch(server_name='0.0.0.0', share=True)