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import gradio as gr
from transformers import pipeline
import spaces
# Load the pipeline (lazy-load the model to save resources)
@spaces.GPU
def load_model():
return pipeline(
"text-to-image",
model="stabilityai/stable-diffusion-2-1",
torch_dtype="float16" # Ensure compatibility with ZeroGPU
)
# Initialize the pipeline
model = load_model()
# Function to generate images
@spaces.GPU
def generate_image(prompt, guidance_scale=7.5):
print(f"Generating image for prompt: {prompt}")
images = model(prompt, guidance_scale=guidance_scale)
return images[0]
# Gradio interface
interface = gr.Interface(
fn=generate_image,
inputs=[
gr.Textbox(label="Prompt", placeholder="Describe your image..."),
gr.Slider(1, 20, value=7.5, label="Guidance Scale")
],
outputs=gr.Image(label="Generated Image"),
title="Text-to-Image Generator",
description="Generate images from text prompts using Stable Diffusion."
)
# Launch the app
if __name__ == "__main__":
interface.launch(server_name="0.0.0.0", server_port=7860)
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