Instructions to use kebab111/FurryStaber with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kebab111/FurryStaber with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kebab111/FurryStaber", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from kebab111/FurryStaber: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/kebab111/FurryStaber/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://kebab111/FurryStaber/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kebab111/FurryStaber/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- c858c057a7de76658db3be7f1d5875cb00128fbfeb2db4a654fbce0650c73a8a
- Size of remote file:
- 492 MB
- SHA256:
- 07a9b4bda533c731eb7c9ddddbb2903444a2b2e98c47d4260a14e21046f6fa08
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.