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README.md
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from diffusers import UNet2DConditionModel, DiffusionPipeline, LCMScheduler
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unet = UNet2DConditionModel.from_pretrained("latent-consistency/lcm-sdxl", torch_dtype=torch.float16, variant="fp16")
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prompt = "a red car standing on the side of the street"
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image = pipe(prompt, num_inference_steps=4, guidance_scale=8.0).images[0]
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```py
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from diffusers import UNet2DConditionModel, DiffusionPipeline, LCMScheduler
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unet = UNet2DConditionModel.from_pretrained("latent-consistency/lcm-sdxl", torch_dtype=torch.float16, variant="fp16")
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prompt = "a red car standing on the side of the street"
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image = pipe(prompt, num_inference_steps=4, guidance_scale=8.0).images[0]
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```
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