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:
- 8f3b89b4ec084093a48205f621a5d0420ea838de6e7298b037c0e6c921f799a8
- Size of remote file:
- 10.5 MB
- SHA256:
- 0b258147b7c9fc58ebdc215e9ada5bca3e372ee370e2e8e98f26429dbfab1d96
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