Instructions to use SidXXD/HAAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SidXXD/HAAD 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/HAAD", dtype=torch.bfloat16, device_map="cuda") prompt = "photo of a sks person" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 6a5f567a7cf22b1934d17f65ed6581697e17223f706813c337a558d0c4472199
- Size of remote file:
- 76.7 MB
- SHA256:
- c427bf79b3c142cab5ff237579adffd49167ae046de8f6f7ade4312fc2007b4b
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