Instructions to use SidXXD/debug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/debug with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SidXXD/debug", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <new1> person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1430c25c0975a5697dd753db26b8534704929c30d5ebae4d61829d61fbc27836
- Size of remote file:
- 2.62 MB
- SHA256:
- 59a6376e532ff56c3c243d6908719df3d87b2fdf7a6b1c09ab0c261ef00b0783
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