Update app.py

app.py

@@ -2,12 +2,11 @@ import gradio as gr
 import numpy as np
 import random
 
-# import spaces #[uncomment to use ZeroGPU]
 from diffusers import DiffusionPipeline
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
+model_repo_id = "stabilityai/sdxl-emoji"  # Updated to use the sdxl-emoji model
 
 if torch.cuda.is_available():
     torch_dtype = torch.float16
@@ -20,8 +19,6 @@ pipe = pipe.to(device)
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
-
-# @spaces.GPU #[uncomment to use ZeroGPU]
 def infer(
     prompt,
     negative_prompt,
@@ -50,11 +47,10 @@ def infer(
 
     return image, seed
 
-
 examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
+    "Smiling face emoji with heart eyes",
+    "Sad face emoji",
+    "A cute cat emoji with a playful expression",
 ]
 
 css = """
@@ -66,7 +62,7 @@ css = """
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
+        gr.Markdown(" # Emoji Generator with Gradio")
 
         with gr.Row():
             prompt = gr.Text(
@@ -105,7 +101,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=512,  # Adjusted to a typical emoji size
                 )
 
                 height = gr.Slider(
@@ -113,7 +109,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,  # Replace with defaults that work for your model
+                    value=512,  # Adjusted to a typical emoji size
                 )
 
             with gr.Row():
@@ -122,7 +118,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
+                    value=7.5,  # Adjusted for more focused generation
                 )
 
                 num_inference_steps = gr.Slider(
@@ -130,7 +126,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=2,  # Replace with defaults that work for your model
+                    value=25,  # Adjusted for better quality generation
                 )
 
         gr.Examples(examples=examples, inputs=[prompt])
@@ -151,4 +147,4 @@ with gr.Blocks(css=css) as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()