Create app.py

app.py

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+import gradio as gr
+from diffusers import DiffusionPipeline
+
+# Load the diffusion pipeline
+pipeline = DiffusionPipeline.from_pretrained("sd-community/sdxl-flash-mini")
+
+def generate_image(prompt, num_inference_steps=50, guidance_scale=7.5):
+    # Generate image based on prompt
+    image = pipeline(prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale).images[0]
+    return image
+
+# Create Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# sdxl-flash-mini")
+    
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here")
+            num_inference_steps = gr.Slider(label="Number of Inference Steps", minimum=1, maximum=100, value=50)
+            guidance_scale = gr.Slider(label="Guidance Scale", minimum=1.0, maximum=10.0, value=7.5)
+            generate_button = gr.Button("Generate Image")
+        
+        with gr.Column():
+            output_image = gr.Image(label="Generated Image")
+
+    generate_button.click(
+        fn=generate_image,
+        inputs=[prompt, num_inference_steps, guidance_scale],
+        outputs=output_image
+    )
+
+# Launch the Gradio interface
+demo.launch()