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Add UNet weights in diffusers format

#2
by dn6 HF staff - opened
base: refs/heads/main
←
from: refs/pr/2
Discussion Files changed
+330
-0
Files changed (9) hide show
  1. README.md +26 -0
  2. unet_1_step_x0/config.json +73 -0
  3. unet_1_step_x0/diffusion_pytorch_model.safetensors +3 -0
  4. unet_2_step/config.json +73 -0
  5. unet_2_step/diffusion_pytorch_model.safetensors +3 -0
  6. unet_4_step/config.json +73 -0
  7. unet_4_step/diffusion_pytorch_model.safetensors +3 -0
  8. unet_8_step/config.json +73 -0
  9. unet_8_step/diffusion_pytorch_model.safetensors +3 -0
README.md CHANGED
@@ -90,6 +90,32 @@ pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, times
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  pipe("A girl smiling", num_inference_steps=1, guidance_scale=0).images[0].save("output.png")
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  ```
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94
  ## ComfyUI Usage
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  pipe("A girl smiling", num_inference_steps=1, guidance_scale=0).images[0].save("output.png")
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  ```
92
 
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+ ## Loading weights into the Diffusers `UNet2DConditionModel`
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+
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+ It is also possible to directly load the weights into the `UNet2DConditionModel`. This is useful if you want to avoid downloading the original SDXL UNet or preload different UNets in RAM and then hot-swap them in VRAM.
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+
97
+ ```python
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+ import torch
99
+ from diffusers import (
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+ EulerDiscreteScheduler,
101
+ StableDiffusionXLPipeline,
102
+ UNet2DConditionModel,
103
+ )
104
+
105
+ base = "stabilityai/stable-diffusion-xl-base-1.0"
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+ repo_id = "ByteDance/SDXL-Lightning"
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+
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+ # Load model.
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+ unet = UNet2DConditionModel.from_pretrained(repo_id, subfolder="unet_4_step", torch_dtype=torch.float16)
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+ pipe = StableDiffusionXLPipeline.from_pretrained(base, unet=unet, torch_dtype=torch.float16, variant="fp16")
111
+
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+ # Ensure sampler uses "trailing" timesteps and "sample" prediction type.
113
+ pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
114
+ pipe.enable_model_cpu_offload()
115
+
116
+ # Ensure using the same inference steps as the loaded model and CFG set to 0.
117
+ pipe("A girl smiling", num_inference_steps=4, guidance_scale=0).images[0].save("output.png")
118
+ ```
119
 
120
  ## ComfyUI Usage
121
 
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