Update app.py

app.py

@@ -0,0 +1,39 @@
+import gradio as gr
+import torch
+from diffusers import StableDiffusionXLPipeline, DPMSolverSinglestepScheduler
+from PIL import Image
+
+# Load the Stable Diffusion XL model
+def load_model():
+    pipe = StableDiffusionXLPipeline.from_pretrained(
+        "sd-community/sdxl-flash",
+        torch_dtype=torch.float16,
+        low_cpu_mem_usage=True
+    )# .to("cuda")
+    pipe.scheduler = DPMSolverSinglestepScheduler.from_config(
+        pipe.scheduler.config,
+        timestep_spacing="trailing"
+    )
+    return pipe
+
+# Function to generate images
+def generate_image(prompt, num_inference_steps=3, guidance_scale=1):
+    pipe = load_model()
+    image = pipe(prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale).images[0]
+    return image
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=generate_image,
+    inputs=[
+        gr.Textbox(label="Enter a prompt for the image"),
+        # gr.Slider(minimum=1, maximum=50, label="Number of Inference Steps"),
+        # gr.Slider(minimum=1, maximum=20, label="Guidance Scale")
+    ],
+    outputs="image",
+    title="Stable Diffusion XL Text-to-Image",
+    description="Generate images from text prompts using Stable Diffusion XL."
+)
+
+# Launch the Gradio app
+iface.launch()