Instructions to use Niggendar/DimMoax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Niggendar/DimMoax 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/DimMoax", 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:
- 206e729864cfb0fb10a4713f3be216b0853dd07e5a906da80a399e1910b0f321
- Size of remote file:
- 246 MB
- SHA256:
- c167cfbe80baf61cfbe9f42a5fad69ac273c622664b94b856133fb1f6c1b7871
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