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import gradio as gr
import pandas as pd
def value_func():
return pd.DataFrame({"Name": ["[SD-XL](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0)", "[SSD-1B](https://huggingface.co/segmind/SSD-1B)", "[Delibarate-V3](https://huggingface.co/stablediffusionapi/deliberate-v3)", "[DALLE•3-XL](https://huggingface.co/openskyml/dalle-3-xl)", "[Midjourney-V4-XL](https://huggingface.co/openskyml/midjourney-v4-xl)"],
"LCM-LoRA": ["[True](https://huggingface.co/openskyml/lcm-lora-stable-diffusion-xl)", "[True](https://huggingface.co/openskyml/lcm-lora-ssd-1b)", "False", "False", "False"],
"Dev by": ["[StabilityAI](https://huggingface.co/stabilityai)", "[Segmind AI](https://huggingface.co/segmind)", "[XpucT](https://huggingface.co/XpucT)", "[OpenSkyML](https://huggingface.co/openskyml)", "[OpenSkyML](https://huggingface.co/openskyml)"],
})
with gr.Blocks() as demo:
gr.Markdown("""
# 🎖️ Diffusion Models Leaderboard
🤗 Using this simple table you can familiarize yourself with good Diffusion models on HuggingFace.
🤩 The Leaderboard is made by OpenSkyML and is based on subjective opinion.
""")
gr.DataFrame(value=value_func)
demo.launch(show_api=False) |