Create app.py

app.py

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+import gradio as gr
+from diffusers import DiffusionPipeline
+
+# Load the diffusion model
+pipe = DiffusionPipeline.from_pretrained("ByteDance/SDXL-Lightning")
+
+def generate_image(prompt):
+    # Generate the image based on the prompt
+    image = pipe(prompt).images[0]
+    return image
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=generate_image,
+    inputs=gr.inputs.Textbox(label="Enter your prompt", placeholder="e.g., Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"),
+    outputs=gr.outputs.Image(type="pil", label="Generated Image"),
+    title="Image Generation with SDXL-Lightning",
+    description="Enter a prompt to generate an image using the SDXL-Lightning model."
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    iface.launch()