Instructions to use takutan/rnrn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use takutan/rnrn with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("takutan/rnrn", 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:
- de3b9980e1dcf25d3590d6379949cf8f2ec0fdaebae7c6da63a8ab73d4332292
- Size of remote file:
- 62.2 MB
- SHA256:
- d338613a667d193d1be99cae2a638fb6f3ae7a0c5854f204d9dfebffd5be336b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.