Instructions to use GraydientPlatformAPI/bellyuse-nplus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GraydientPlatformAPI/bellyuse-nplus with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GraydientPlatformAPI/bellyuse-nplus", 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
- Xet hash:
- 8f257591df6af34011e28709331e96b7d45ea7af609ed39a6abad4717e754601
- Size of remote file:
- 167 MB
- SHA256:
- ff443ca545bb3937d6f0ea7759f935d1ba1494b5f1977de5972f874de68bb081
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.