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+ # Import the required libraries
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+ from diffusers import StableDiffusionPipeline
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+ import torch
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+ from PIL import Image
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+ import gradio as gr
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+
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+ # Set up the model and device
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+ model_id = "CompVis/stable-diffusion-v1-4"
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+ pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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+
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+ # Move the model to the GPU if available
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+ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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+ pipe.to(device)
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+
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+ # Define a function to generate an image from text
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+ def generate_image(prompt):
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+ # Generate the image
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+ image = pipe(prompt).images[0]
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+
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+ # Return the image
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+ return image
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+
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+ # Create a Gradio interface
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+ demo = gr.Interface(
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+ fn=generate_image,
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+ inputs=[gr.Textbox(label="Text Prompt", placeholder="Enter a text prompt")],
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+ outputs=[gr.Image(label="Generated Image")],
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+ title="Text-to-Image AI",
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+ description="Enter a text prompt to generate an image",
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+ )
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+
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+ # Launch the Gradio interface
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+ demo.launch()