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import gradio as gr | |
import pandas as pd | |
# Load the results | |
elo_df = pd.read_csv("elo-20240326.csv") | |
text_description = """ | |
# 🤼 LLM Colosseum Leaderboard | |
LLM Colosseum is a new way to assess the relative performance of LLMs. We have them play Street Fighter III against each other, and we use the results to calculate their Elo ratings. | |
More info in the LLM Colosseum GitHub [repository](https://github.com/OpenGenerativeAI/llm-colosseum). | |
🎥 Demo of LLMs playing Street Fighter III below the table. | |
""" | |
def show_video(): | |
# Returns the embed code, which Gradio will display using the HTML component | |
return youtube_embed_code | |
youtube_embed_code = '<iframe width="560" height="315" src="https://www.youtube.com/embed/Kk8foX3dm2I?si=5BJNkipqAXl4CRBu" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>' | |
with gr.Blocks( | |
title="LLM Colosseum Leaderboard", | |
) as demo: | |
gr.Markdown(text_description) | |
gr.Dataframe(value=elo_df, interactive=False) | |
gr.Markdown("## Watch a demo of LLMs playing Street Fighter III:") | |
gr.HTML(value=youtube_embed_code) | |
demo.launch() | |