Instructions to use koankoan/lilcyborg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use koankoan/lilcyborg with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("koankoan/lilcyborg", dtype=torch.bfloat16, device_map="cuda") prompt = "lilcyborg" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1e5d2df5225ef3995f4b4c586351aac1fa72a950c4c8ce83e36321a25c39ec14
- Size of remote file:
- 2.13 GB
- SHA256:
- d569989f14200bd020cfb4aa00e5bbf8735753cb0ab091f7a54f3e2a5f5ad0ae
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