Instructions to use isatis/kw with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use isatis/kw with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("isatis/kw", 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
- Xet hash:
- 5bb7535c5efe0b6abf95d6141627943d35f692a42e91bb383c5f6e00f6a36be6
- Size of remote file:
- 492 MB
- SHA256:
- ec3883f2cc6b4a8661212175bb7ccefe9f2309888d3e53c9f274e7de60acc88a
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