Instructions to use RedRocket/furception_vae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use RedRocket/furception_vae 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("RedRocket/furception_vae", 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
Commit History
-
clarify licensing
Verified signaturecccb6c6 -
add pipeline
Verified signaturec540340
-
Update README.md
Verified signaturee66c074 -
Update README.md
Verified signature064795b -
Update README.md
Verified signature775ce4c -
Update README.md
Verified signature5458b76 -
Update README.md
Verified signature6430063 -
Update README.md
Verified signaturefcbce1c -
upload basic examples
Verified signature1919635 -
Create README.md
Verified signature2df88a6 -
Upload folder using huggingface_hub
Verified signature3a51ff7 -
Upload folder using huggingface_hub
Verified signature5722aff -
Upload furception_vae_1-0.safetensors with huggingface_hub
Verified signature7db45e2 -
initial commit
Verified signature6a1d0a0