Instructions to use SidXXD/162 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/162 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/162", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a <v1*> person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- ec3e0d6f72cb40db928c6b0b729700f0edf1c2fce87d86d7d0256c84db0c8b2e
- Size of remote file:
- 76.7 MB
- SHA256:
- b2c360754e0b603d64ec20201abfd5432a4ac1f3dca9e174629d900ff90fa178
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