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:
- 3da5e9eadf355bc78ac1e1a6aad33a59477d10b9ff93e40527e0d2971e589b5e
- Size of remote file:
- 335 MB
- SHA256:
- 5c0df075ef639af93504390fa2261ca51755494b6fc7d5db2f86de518d814335
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