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Create app.py

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  1. app.py +37 -0
app.py ADDED
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+ from diffusers import DiffusionPipeline
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+ import torch
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+
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+ # load both base & refiner
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+ base = DiffusionPipeline.from_pretrained(
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+ "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
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+ )
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+ base.to("cuda")
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+ refiner = DiffusionPipeline.from_pretrained(
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+ "stabilityai/stable-diffusion-xl-refiner-1.0",
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+ text_encoder_2=base.text_encoder_2,
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+ vae=base.vae,
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+ torch_dtype=torch.float16,
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+ use_safetensors=True,
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+ variant="fp16",
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+ )
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+ refiner.to("cuda")
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+
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+ # Define how many steps and what % of steps to be run on each experts (80/20) here
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+ n_steps = 40
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+ high_noise_frac = 0.8
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+
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+ prompt = "A majestic lion jumping from a big stone at night"
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+
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+ # run both experts
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+ image = base(
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+ prompt=prompt,
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+ num_inference_steps=n_steps,
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+ denoising_end=high_noise_frac,
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+ output_type="latent",
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+ ).images
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+ image = refiner(
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+ prompt=prompt,
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+ num_inference_steps=n_steps,
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+ denoising_start=high_noise_frac,
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+ image=image,
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+ ).images[0]