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