Instructions to use code-and-canvas/Walkyrie-1.3B-v2.0-CoreML-float16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use code-and-canvas/Walkyrie-1.3B-v2.0-CoreML-float16 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("code-and-canvas/Walkyrie-1.3B-v2.0-CoreML-float16", 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:
- 4dbd8743d38a65740e5a60f75370c403cfad58b5c4a88653aa8075f79fdd7c23
- Size of remote file:
- 508 MB
- SHA256:
- 8da83431220b1e9e55e04f3f84a6d5974d1de614b24fad99a3d0c399b0efd70a
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