Instructions to use dkackman/DreamShaper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dkackman/DreamShaper with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dkackman/DreamShaper", 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:
- 0c3d468236c5b88073d305b47df8d8f77880c715a8dbb16eb6d33d102b511c8e
- Size of remote file:
- 492 MB
- SHA256:
- 039df8aa5e5967da179fdb912bf9c307a3f9582ed96a888b900d1d8e6be5832b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.