Update app.py

app.py

@@ -1,11 +1,20 @@
 import gradio as gr
-from diffusers import AutoPipelineForText2Image
+import numpy as np
+import random
+from diffusers import DiffusionPipeline
 import torch
 
-# Load the SDXL-Turbo model
-pipe = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
-pipe.to("cuda")
+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)
+    
 # Define the image generation function
 def generate_image(prompt, steps, guidance):
     image = pipe(prompt=prompt, num_inference_steps=steps, guidance_scale=guidance).images[0]