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README.md
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@@ -25,7 +25,7 @@ Please always use the correct checkpoint for the corresponding inference steps.
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```python
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import torch
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from diffusers import StableDiffusionXLPipeline, EulerDiscreteScheduler
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from huggingface_hub import hf_hub_download
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base = "stabilityai/stable-diffusion-xl-base-1.0"
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ckpt = "sdxl_lightning_4step_unet.pth" # Use the correct ckpt for your step setting!
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# Load model.
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# Ensure sampler uses "trailing" timesteps.
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pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
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```python
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import torch
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from diffusers import StableDiffusionXLPipeline, EulerDiscreteScheduler
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from huggingface_hub import hf_hub_download
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base = "stabilityai/stable-diffusion-xl-base-1.0"
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ckpt = "sdxl_lightning_1step_unet_x0.pth" # Use the correct ckpt for your step setting!
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# Load model.
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# Ensure sampler uses "trailing" timesteps and "sample" prediction type.
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pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing", prediction_type="sample")
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### 1-Step UNet
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ComfyUI does not support changing model formulation to x0-prediction, so it is not usable in ComfyUI yet. Hopefully ComfyUI
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```python
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import torch
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from diffusers import StableDiffusionXLPipeline, UNet2DConditionModel, EulerDiscreteScheduler
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from huggingface_hub import hf_hub_download
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base = "stabilityai/stable-diffusion-xl-base-1.0"
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ckpt = "sdxl_lightning_4step_unet.pth" # Use the correct ckpt for your step setting!
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# Load model.
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unet = UNet2DConditionModel.from_config(base, subfolder="unet").to("cuda", torch.float16)
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unet.load_state_dict(torch.load(hf_hub_download(repo, ckpt), map_location="cuda"))
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pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float16, variant="fp16").to("cuda")
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# Ensure sampler uses "trailing" timesteps.
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pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
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```python
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import torch
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from diffusers import StableDiffusionXLPipeline, UNet2DConditionModel, EulerDiscreteScheduler
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from huggingface_hub import hf_hub_download
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base = "stabilityai/stable-diffusion-xl-base-1.0"
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ckpt = "sdxl_lightning_1step_unet_x0.pth" # Use the correct ckpt for your step setting!
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# Load model.
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unet = UNet2DConditionModel.from_config(base, subfolder="unet").to("cuda", torch.float16)
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unet.load_state_dict(torch.load(hf_hub_download(repo, ckpt), map_location="cuda"))
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pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float16, variant="fp16").to("cuda")
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# Ensure sampler uses "trailing" timesteps and "sample" prediction type.
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pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing", prediction_type="sample")
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### 1-Step UNet
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ComfyUI does not support changing the model formulation to x0-prediction, so it is not usable in ComfyUI yet. Hopefully, ComfyUI will get updated soon.
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