Instructions to use lora-library/saz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lora-library/saz with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("andite/anything-v4.0", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lora-library/saz") prompt = "saz" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 0c47d929fc79855cd8a3aae73d4e16073d14ec7857e58c3f3b8b9b1c05652a7b
- Size of remote file:
- 3.29 MB
- SHA256:
- bdd6de8bacc2d6506d3f506cbb650aac9af7b7c3859c50bc2dcc2ab3efeef844
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