Instructions to use nubby/Yume-Grimgar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nubby/Yume-Grimgar with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nubby/Yume-Grimgar", 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
- Xet hash:
- 1597ab94543e4c2b880f0dbbc110b5f02d8213decd0d5ee3b2937a71427eed99
- Size of remote file:
- 492 MB
- SHA256:
- 5d1b633a9723579eb7e97e4ae7bb59bfbb80838e64a26babffcf55fee5845b94
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.