Instructions to use WeiChow/AnySD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WeiChow/AnySD 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("WeiChow/AnySD", 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
- Xet hash:
- e2c63d6cd5c0fe1526f06b9dd4af7e4a04c1a374ebb3ccfac19f6dfc69e2d4f4
- Size of remote file:
- 44.2 kB
- SHA256:
- 6d85f4ae06fb6d461dcb9a4850503fe4a4d192e648c89fc8ca3036e3b626cdad
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.