Instructions to use Vaelico/Wulver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Vaelico/Wulver with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Vaelico/Wulver", 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
Commit History
21 days ago
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Wulver v0.5
Verified signatureAdd Wulver v0.5 weights (Turbo 1.0 merged, fp8, int8 ConvRot, W4A8 ConvRot, Non-Turbo bf16 / int8 ConvRot), workflow, artist list and checksums. v0.1 files unchanged.c77ac3a
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Add original Wulver v0.1 Non-Turbo BF16 training base
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Update README.md
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License compliance (Krea 2 Community License) + tracked downloads
Verified signatureAdds the verbatim Krea 2 Community License Agreement (LICENSE.md) and the attribution/modification NOTICE required by sections 3.1-3.2; README title begins with 'Krea 2' per 3.1(b); library_name set so Hub counts safetensors downloads; removes the '@artistname' claim (not functional in v0.1).2e72a19
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