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:
- cc348382b655c27536d9210cb62550c92a1f29bfd9125bcc8a18a028a607e0ec
- Size of remote file:
- 686 kB
- SHA256:
- 53f13f2f0357c9b2e76b31da5041243cad66593e25eccdb6b146216d367aaedc
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