Update app.py

app.py

@@ -2,35 +2,26 @@ import gradio as gr
 import numpy as np
 import random
 
-from diffusers import DiffusionPipeline, EulerDiscreteScheduler
+# import spaces #[uncomment to use ZeroGPU]
+from diffusers import DiffusionPipeline
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "black-forest-labs/FLUX.1-schnell"
+model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
 
-# Choose dtype
-torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
+if torch.cuda.is_available():
+    torch_dtype = torch.float16
+else:
+    torch_dtype = torch.float32
 
-# Load scheduler first
-scheduler = EulerDiscreteScheduler.from_pretrained(
-    model_repo_id,
-    subfolder="scheduler"
-)
-
-# Load pipeline w/ custom scheduler
-pipe = DiffusionPipeline.from_pretrained(
-    model_repo_id,
-    scheduler=scheduler,
-    torch_dtype=torch_dtype
-).to(device)
-
-# Speed tweaks for CPU / weak GPU
-pipe.enable_attention_slicing()
-pipe.enable_sequential_cpu_offload()
+pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
+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,
@@ -50,10 +41,10 @@ def infer(
     image = pipe(
         prompt=prompt,
         negative_prompt=negative_prompt,
-        width=width,
-        height=height,
         guidance_scale=guidance_scale,
         num_inference_steps=num_inference_steps,
+        width=width,
+        height=height,
         generator=generator,
     ).images[0]
 
@@ -61,9 +52,9 @@ def infer(
 
 
 examples = [
-    "Astronaut in the jungle, hyper-detailed",
-    "A green horse in space",
-    "Cyberpunk ramen bowl with neon lights",
+    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
+    "An astronaut riding a green horse",
+    "A delicious ceviche cheesecake slice",
 ]
 
 css = """
@@ -75,7 +66,7 @@ css = """
 
 with gr.Blocks(css=css) as demo:
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Flux Schnell Inference 🎨🔥")
+        gr.Markdown(" # Text-to-Image Gradio Template")
 
         with gr.Row():
             prompt = gr.Text(
@@ -85,6 +76,7 @@ with gr.Blocks(css=css) as demo:
                 placeholder="Enter your prompt",
                 container=False,
             )
+
             run_button = gr.Button("Run", scale=0, variant="primary")
 
         result = gr.Image(label="Result", show_label=False)
@@ -93,7 +85,7 @@ with gr.Blocks(css=css) as demo:
             negative_prompt = gr.Text(
                 label="Negative prompt",
                 max_lines=1,
-                placeholder="bad quality, blurry",
+                placeholder="Enter a negative prompt",
                 visible=True,
             )
 
@@ -110,17 +102,18 @@ with gr.Blocks(css=css) as demo:
             with gr.Row():
                 width = gr.Slider(
                     label="Width",
-                    minimum=256,
+                    minimum=64,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=512,
+                    value=1024,  # Replace with defaults that work for your model
                 )
+
                 height = gr.Slider(
                     label="Height",
-                    minimum=256,
+                    minimum=64,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=512,
+                    value=1024,  # Replace with defaults that work for your model
                 )
 
             with gr.Row():
@@ -129,19 +122,18 @@ with gr.Blocks(css=css) as demo:
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=0.0,
+                    value=1,  # Replace with defaults that work for your model
                 )
 
                 num_inference_steps = gr.Slider(
                     label="Number of inference steps",
                     minimum=1,
-                    maximum=20,
+                    maximum=50,
                     step=1,
-                    value=4,
+                    value=7,  # Replace with defaults that work for your model
                 )
 
         gr.Examples(examples=examples, inputs=[prompt])
-
     gr.on(
         triggers=[run_button.click, prompt.submit],
         fn=infer,
@@ -159,4 +151,4 @@ with gr.Blocks(css=css) as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()