| 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() | |