Instructions to use SidXXD/Clean-f_26 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/Clean-f_26 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/Clean-f_26", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a sks person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_custom_diffusion_weights.bin from SidXXD/Clean-f_26: direct link, hf CLI and curl.
- Browser
- Download file 76.7 MB
-
https://huggingface.co/SidXXD/Clean-f_26/resolve/main/pytorch_custom_diffusion_weights.bin
- Command line
-
hf download hf://SidXXD/Clean-f_26/pytorch_custom_diffusion_weights.bin
-
curl -L -o pytorch_custom_diffusion_weights.bin https://huggingface.co/SidXXD/Clean-f_26/resolve/main/pytorch_custom_diffusion_weights.bin
76.7 MB
- Xet hash:
- 49eef4f46378be5ad4004c32a68cff028595e8841cb967d0ddfc832dd16f5f03
- Size of remote file:
- 76.7 MB
- SHA256:
- a58b05694966ce769653ecec88d74afaf6220570e8453a8f5a447923ddbe3139
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