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1. ν‰κ°€μ μˆ˜ 0 은 평가 μ—†μŒμœΌλ‘œ μ²˜λ¦¬ν•œλ‹€. 2. μ»¬λŸΌμ •λ¦¬ 및 순번 μΆ”κ°€ 3. About νŽ˜μ΄μ§€
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import gradio as gr
import pandas as pd
import requests
from src.about import (
INTRODUCTION_TEXT,
LLM_BENCHMARKS_TEXT,
TITLE,
)
from src.display.css_html_js import custom_css
def get_evaluation():
response = requests.get("http://aim100.qinference.com/api/leaderboard/list")
data_json = response.json()
df = pd.DataFrame(data_json)
for col in df.columns:
df.loc[df[col] == 0, col] = '-'
df.insert(0, 'No', df.reset_index().index + 1)
ret = df.drop(columns='nodeSeq').rename(columns={'modelName': 'Model'})
ret.columns = [x.capitalize() for x in ret.columns]
return ret
leaderboard = gr.Blocks(css=custom_css)
with leaderboard:
gr.HTML(TITLE)
gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
with gr.Tabs(elem_classes="tab-buttons") as tabs:
with gr.TabItem("πŸ… LLM Benchmark", elem_id="llm-benchmark-tab-table", id=0):
leaderboard_table = gr.components.Dataframe(
value=get_evaluation(),
elem_id="leaderboard-table",
interactive=False,
visible=True,
)
with gr.TabItem("πŸ“ About", elem_id="llm-benchmark-tab-table", id=2):
gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
leaderboard.queue(default_concurrency_limit=40).launch()