Instructions to use Niggendar/DimSTS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Niggendar/DimSTS with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Niggendar/DimSTS", 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:
- 118937a39edfe78d46f0676e63eb13792164971bb93cf9e134fbb0dd20ee1d0e
- Size of remote file:
- 246 MB
- SHA256:
- 23c5eb7ed46a311d75076d00d1fa396f699be960f3f2ef90ed4700a10ef94899
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