Update app.py

app.py

@@ -42,8 +42,8 @@ interface = gr.Interface(
         gr.Text(label="Negative Prompt"),
         gr.Slider(minimum=10, maximum=100, value=30, step=1, label="Number of Inference Steps"),
         gr.Slider(minimum=1, maximum=20, value=6, step=0.1, label="Guidance Scale"),
-        gr.Slider(minimum=64, maximum=2048, value=1024, step=64, label="Height"),
-        gr.Slider(minimum=64, maximum=2048, value=1024, step=64, label="Width"),
+        gr.Slider(minimum=64, maximum=1024, value=1024, step=64, label="Height"),
+        gr.Slider(minimum=64, maximum=1024, value=1024, step=64, label="Width"),
     ],
     outputs=gr.Image(label="Generated Image"),
     title="PixArt Sigma Image Generation",
@@ -52,6 +52,8 @@ interface = gr.Interface(
 PixArt-Sigma achieves superior image quality and alignment with prompts compared to previous models like [PixArt-alpha](https://github.com/PixArt-alpha/PixArt-sigma). It does so efficiently, evolving from PixArt-alpha through a process termed weak-to-strong training - leveraging higher quality data and an improved attention mechanism.
 
 With just 0.6 billion parameters, PixArt-Sigma reaches new heights in text-to-image generation. Output stunning, intricate 4K images for posters, wallpapers, concept art, and more. Guide the model with descriptive prompts and fine-tune parameters like guidance scale and number of inference steps.
+
+For more information, visit the original [repository](https://github.com/PixArt-alpha/PixArt-sigma) and follow the HF Space creator on Twitter at [@artificialguybr](https://twitter.com/artificialguybr).
 """,
 )