Update app.py

app.py

@@ -2,9 +2,22 @@ import gradio as gr
 import pandas as pd
 
 def value_func():
-    return pd.DataFrame({"Name": ["SD-XL", "SSD-1B", "Delibarate"], "LCM-LoRA": ["True", "True", "False"]})
+    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()
+demo.launch(show_api=False)