Update app.py

app.py

@@ -1,23 +1,18 @@
+#Lisence: Apache 2.0
 import gradio as gr
 import numpy as np
 import random
 from diffusers import DiffusionPipeline
 import torch
+import spaces
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
-
-if torch.cuda.is_available():
-    torch.cuda.max_memory_allocated(device=device)
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
-    pipe.enable_xformers_memory_efficient_attention()
-    pipe = pipe.to(device)
-else: 
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
-    pipe = pipe.to(device)
+pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+pipe = pipe.to("cuda")
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
+@spaces.GPU
 def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
 
     if randomize_seed:
@@ -37,12 +32,6 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     
     return image
 
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
-
 css="""
 #col-container {
     margin: 0 auto;
@@ -50,17 +39,11 @@ css="""
 }
 """
 
-if torch.cuda.is_available():
-    power_device = "GPU"
-else:
-    power_device = "CPU"
-
 with gr.Blocks(css=css) as demo:
     
     with gr.Column(elem_id="col-container"):
         gr.Markdown(f"""
         # Text-to-Image Gradio Template
-        Currently running on {power_device}.
         """)
         
         with gr.Row():
@@ -131,11 +114,6 @@ with gr.Blocks(css=css) as demo:
                     step=1,
                     value=2,
                 )
-        
-        gr.Examples(
-            examples = examples,
-            inputs = [prompt]
-        )
 
     run_button.click(
         fn = infer,
@@ -143,4 +121,4 @@ with gr.Blocks(css=css) as demo:
         outputs = [result]
     )
 
-demo.queue().launch()
+demo.queue().launch()