Instructions to use kukidevalml/Z-Image-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kukidevalml/Z-Image-Lora 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,Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kukidevalml/Z-Image-Lora") prompt = "Alexandra Chando (vrtlAlexandraChando)" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
-ID.webp)
- Xet hash:
- 7d8c4fbf21d8065a9fde352e3eb2945ad04208ac7d88bfdbf505b2ea5f378488
- Size of remote file:
- 440 kB
- SHA256:
- d439c6dd0f04c51003d8aee0bad07f7495bb3f1bed2b19e90b626f9c9d613308
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