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:
- a0975b91813aca261272c46ebe5bc24419544e3bbdc27f9526eb3b2e9784d543
- Size of remote file:
- 3.46 GB
- SHA256:
- eb49869c0c00bd518e5f34ff8cda9759b8cfa2774454ebc83467f7516b4d382b
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