Instructions to use moonrabbit256/2K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use moonrabbit256/2K with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("moonrabbit256/2K", 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:
- 6a9a96cad1eacccd62e0cc2c8522ad23c73112ef85393e3c9be6bfd4ba50206f
- Size of remote file:
- 246 MB
- SHA256:
- 7d67e7c14470e1621985e0377b1e8685b38c5f89a398d39cfe222b61fc80de65
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.