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test.py
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import torch
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from diffusers import AutoPipelineForImage2Image
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from diffusers.utils import make_image_grid, load_image
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pipeline = AutoPipelineForImage2Image.from_pretrained(
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"stable-diffusion-v1-5/stable-diffusion-v1-5", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
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)
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pipeline.enable_model_cpu_offload()
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# remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed
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pipeline.enable_xformers_memory_efficient_attention()
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# prepare image
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url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/img2img-init.png"
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init_image = load_image(url)
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prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
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# pass prompt and image to pipeline
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image = pipeline(prompt, image=init_image).images[0]
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make_image_grid([init_image, image], rows=1, cols=2)
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