Instructions to use sivar/legostyle1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sivar/legostyle1-5 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("sivar/legostyle1-5", 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 vae/diffusion_pytorch_model.bin from sivar/legostyle1-5: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/sivar/legostyle1-5/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://sivar/legostyle1-5/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/sivar/legostyle1-5/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- 778dc1c69347ac5285006812c018bacd75f3c015b0a876314d6c5878ba554169
- Size of remote file:
- 335 MB
- SHA256:
- 36bb8e1b54aba3a0914eb35fba13dcb107e9f18d379d1df2158732cd4bf56a94
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.