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import gradio as gr
from diffusers import DiffusionPipeline
# Load the diffusion pipeline
pipe = DiffusionPipeline.from_pretrained("ByteDance/AnimateDiff-Lightning")
def generate_image(prompt):
# Generate the image from the prompt
image = pipe(prompt).images[0]
return image
# Create a Gradio interface
iface = gr.Interface(
fn=generate_image,
inputs=gr.Textbox(label="Enter your prompt", placeholder="e.g. Astronaut in a jungle"),
outputs=gr.Image(label="Generated Image"),
title="Diffusion Pipeline Image Generator",
description="Generate images using a diffusion pipeline based on your prompts."
)
if __name__ == "__main__":
iface.launch()
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