cleandift

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license:mit
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CompVis
Image Model
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Quick Summary

AI model with specialized capabilities.

Code Examples

python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
python
from diffusers import UNet2DConditionModel
from huggingface_hub import hf_hub_download

unet = UNet2DConditionModel.from_pretrained("stabilityai/stable-diffusion-2-1", subfolder="unet")
ckpt_pth = hf_hub_download(repo_id="CompVis/cleandift", filename="cleandift_sd21_unet.safetensors")
state_dict = load_file(ckpt_pth)
unet.load_state_dict(state_dict, strict=True)
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}
Citationbibtex
@misc{stracke2024cleandiftdiffusionfeaturesnoise,
      title={CleanDIFT: Diffusion Features without Noise}, 
      author={Nick Stracke and Stefan Andreas Baumann and Kolja Bauer and Frank Fundel and Björn Ommer},
      year={2024},
      eprint={2412.03439},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2412.03439}, 
}

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