Instructions to use Niggendar/GsusGem with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Niggendar/GsusGem 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/GsusGem", 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:
- 07302aa6a06349af4aa3c589e03e6398a89c3e4c36439fb7f62e2774b76e3d20
- Size of remote file:
- 246 MB
- SHA256:
- d849cbfec916fb8fbebc66bafb0ad5d538df99aff846762892a21c25b1a37195
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