Instructions to use konapieces/VoidnoiseCore with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use konapieces/VoidnoiseCore with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("konapieces/VoidnoiseCore", 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
Download images/R1733/logo.png from konapieces/VoidnoiseCore: direct link, hf CLI and curl.
- Browser
- Download file 1.37 MB
-
https://huggingface.co/konapieces/VoidnoiseCore/resolve/main/images/R1733/logo.png
- Command line
-
hf download hf://konapieces/VoidnoiseCore/images/R1733/logo.png
-
curl -L -o logo.png https://huggingface.co/konapieces/VoidnoiseCore/resolve/main/images/R1733/logo.png
1.37 MB

- Xet hash:
- 25c0272db7658f8ea8b8c4e2a5eefc3aa36ea995c2d1a53ce642f71a740ebcb3
- Size of remote file:
- 1.37 MB
- SHA256:
- 0e1c39b81aac9baa5873fc6af2705cd1c28a8a165d8518baad3eb276363e2116
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