Instructions to use Muapi/standing-split with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/standing-split with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OnomaAIResearch/Illustrious-xl-early-release-v0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/standing-split") 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:
- e292dc9748a9b93e0e8868fe748c4d4f9d6ba45df32e2ee0f461e181267e2c55
- Size of remote file:
- 1.11 MB
- SHA256:
- a95855b7575d22dd59578a2273f04d2bab57c93ea5ad98db2afd8a4e80558ce1
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