Instructions to use atomato/capybara with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use atomato/capybara with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("atomato/capybara", torch_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:
- d794cba0390b8dff091f28dfdb38d4ff7e9b23d079c96f561d4b06e5e3556f5a
- Size of remote file:
- 3.44 GB
- SHA256:
- d3cd78082f0c339b595c8494f32513575988bf217dbd5e5a9e5ae845cad6f050
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