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Create app.py
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app.py
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from diffusers import DiffusionPipeline, LCMScheduler
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import gradio as gr
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pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0").to("cuda")
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pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
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pipe.load_lora_weights("latent-consistency/lcm-lora-sdxl")
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def generate_images(prompt, batch_size):
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images = []
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for _ in range(batch_size):
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results = pipe(
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prompt=prompt,
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num_inference_steps=4,
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guidance_scale=1.4,
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)
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images.append(results.images[0])
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return images
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iface = gr.Interface(
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fn=generate_images,
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inputs=[
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gr.Textbox(label="Prompt"),
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gr.Slider(label="Batch Size", minimum=1, maximum=12, step=1, value=1)
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],
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outputs=gr.Gallery(label="Generated Images"),
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title="SuperFast SDXL Generation."
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)
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iface.launch()
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