Instructions to use grugger/chubas with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use grugger/chubas with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("grugger/chubas", 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:
- 9c1008af0b7694279cc0204aa891b03588e38cf84da6089e8e5170294409ab69
- Size of remote file:
- 2.13 GB
- SHA256:
- 40711e9185d860bc0364b47a5bfaea9313bc27447e82fccb24989d3a19e7bb5c
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