Instructions to use LottePeisch/2dn-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LottePeisch/2dn-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LottePeisch/2dn-Diffusers", 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
- Draw Things
- DiffusionBee
- Xet hash:
- ca300312bd3680bcb4e263db1347a6d22d4a5af116f0da9a5200c5ec9118866b
- Size of remote file:
- 167 MB
- SHA256:
- fdcaefcec4b2e6010a985bd6a21e505a5fea2aacd787854d38e849517d91b847
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.