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import gradio as gr
from diffusers import DiffusionPipeline
import os
os.environ['HF_HOME'] = '/blabla/cache/'
# Load the diffusion model
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev")
def generate_image(prompt):
# Generate the image based on the prompt
image = pipe(prompt).images[0]
return image
# Create a Gradio interface using the new component style
iface = gr.Interface(
fn=generate_image,
inputs=gr.Textbox(label="Enter your prompt", placeholder="e.g., Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"),
outputs=gr.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() |