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import gradio as gr
import pandas as pd
data = {
"Model": [
"MiniGPT-5", "EMU-2", "GILL", "Anole",
"GPT-4o - Openjourney", "GPT-4o - SD-3", "GPT-4o - SD-XL", "GPT-4o - Flux",
"Gemini-1.5 - Openjourney", "Gemini-1.5 - SD-3", "Gemini-1.5 - SD-XL", "Gemini-1.5 - Flux",
"LLAVA-34b - Openjourney", "LLAVA-34b - SD-3", "LLAVA-34b - SD-XL", "LLAVA-34b - Flux",
"Qwen-VL-70b - Openjourney", "Qwen-VL-70b - SD-3", "Qwen-VL-70b - SD-XL", "Qwen-VL-70b - Flux"
],
"Situational analysis": [
47.63, 39.65, 46.72, 48.95,
53.05, 53.00, 56.12, 54.97,
48.08, 47.48, 49.43, 47.07,
54.12, 54.72, 55.97, 54.23,
52.73, 54.98, 52.58, 54.23
],
"Project-based learning": [
55.12, 46.12, 57.57, 59.05,
71.40, 71.20, 73.25, 68.80,
67.93, 68.70, 71.85, 68.33,
73.47, 72.55, 74.60, 71.32,
71.63, 71.87, 73.57, 69.47
],
"Multi-step reasoning": [
42.17, 50.75, 39.33, 51.72,
53.67, 53.67, 53.67, 53.67,
60.05, 60.05, 60.05, 60.05,
47.28, 47.28, 47.28, 47.28,
55.63, 55.63, 55.63, 55.63
],
"AVG": [
50.92, 45.33, 51.58, 55.22,
63.65, 63.52, 65.47, 62.63,
61.57, 61.87, 64.15, 61.55,
63.93, 63.57, 65.05, 62.73,
64.05, 64.75, 65.12, 63.18
]
}
df = pd.DataFrame(data)
def leaderboard():
return df
interface = gr.Interface(fn=leaderboard, inputs=[], outputs=gr.Dataframe())
interface.launch()
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