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:
- f2fb714d9903d655f9883af73f73fd8ff74886c69e0f10f18190004ba64ebc9c
- Size of remote file:
- 3.29 MB
- SHA256:
- 1a2accedebf01999980d93081abbe446cb0c3733cde4a6756f79a4ebfd5075ba
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