Instructions to use DeverStyle/Z-Image-loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DeverStyle/Z-Image-loras with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("DeverStyle/Z-Image-loras") prompt = "Arcane style samples" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 5780c846a5f568b508a3a38e30fe3bf3d1ec54aafcefbb3a259bad07ee1d9574
- Size of remote file:
- 4.43 MB
- SHA256:
- dbcb7fbc5dfbb496d79bde85abc323f6fd552c88903d28f8d22d6460010c5bf9
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