Instructions to use plasmo/woolitize with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use plasmo/woolitize with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("plasmo/woolitize", dtype=torch.bfloat16, device_map="cuda") prompt = "woolitize " image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from plasmo/woolitize: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/plasmo/woolitize/resolve/refs%2Fpr%2F2/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://plasmo/woolitize@refs/pr/2/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/plasmo/woolitize/resolve/refs%2Fpr%2F2/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 98724ea2b455185cbab66203ed3843a8dc8661e125c3b93afaa387c9ae450ca3
- Size of remote file:
- 3.44 GB
- SHA256:
- 98e9035993688215a548eceac4edc6c40caaff998991abca2179992956c767ae
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.