Instructions to use CSWRY/VOSR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CSWRY/VOSR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CSWRY/VOSR", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download stable-diffusion-2-1-base/vae/diffusion_pytorch_model.bin from CSWRY/VOSR: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/CSWRY/VOSR/resolve/refs%2Fpr%2F2/stable-diffusion-2-1-base/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://CSWRY/VOSR@refs/pr/2/stable-diffusion-2-1-base/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/CSWRY/VOSR/resolve/refs%2Fpr%2F2/stable-diffusion-2-1-base/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 61555a981781251699f4082032aa464594906dfb8d2007f58ba3280d696f710b
- Size of remote file:
- 335 MB
- SHA256:
- 1b4889b6b1d4ce7ae320a02dedaeff1780ad77d415ea0d744b476155c6377ddc
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