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from diffusers import StableDiffusionXLPipeline
import torch
import gradio as gr
# Load the Stable Diffusion XL model
pipeline = StableDiffusionXLPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
).to("cuda")
def generate_image(prompt, prompt_2):
# Generate the image based on the prompts
image = pipeline(prompt=prompt, prompt_2=prompt_2).images[0]
# Convert the PIL image to a format that Gradio can display
return image
# Define the Gradio interface
iface = gr.Interface(fn=generate_image,
inputs=[gr.Textbox(label="Prompt 1: Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"),
gr.Textbox(label="Prompt 2: Van Gogh painting")],
outputs="image",
title="Stable Diffusion XL Image Generator",
description="Generate images with Stable Diffusion XL based on two prompts.")
# Launch the Gradio app
iface.launch()
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