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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- be9ad1cfcb4866f16f9af6fdb9f4cd74b92142b068c718696a8a828e4de3065f
- Size of remote file:
- 1.39 GB
- SHA256:
- 6af08fff6d33a4bd56cd221e4d28a306cf67c72d1ac1498ef722fbca0787a84f
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