Instructions to use maximalmargin/katz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use maximalmargin/katz with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("maximalmargin/katz", 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:
- acf3cb6fd1e1a415fd37559a05984a638aad955cfeadc59314841598acee3947
- Size of remote file:
- 3.46 GB
- SHA256:
- ec73fac1c783f3999cff1517a0c9744728a060f447ca61c7cc2a56e89a3e65e5
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