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--- |
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library_name: peft |
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tags: |
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- lora |
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--- |
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```py |
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from diffusers import LCMScheduler, DiffusionPipeline |
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import torch |
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import PIL.Image |
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import requests |
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pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16, variant="fp16") |
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pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config) |
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# load and fuse lcm lora |
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pipe.load_lora_weights("latent-consistency/lcm-lora-sdv1-5") |
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pipe.fuse_lora() |
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pipe.to(device="cuda") |
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prompt = "a red Porsche" |
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torch.manual_seed(0) |
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# make sure to use `guidance_scale=1.0` to disable CFG |
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image = pipe(prompt=prompt, num_inference_steps=4, guidance_scale=1.0).images[0] |
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``` |
