Instructions to use boyarkinn/kazumi_zimage_lora_3000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use boyarkinn/kazumi_zimage_lora_3000 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("boyarkinn/kazumi_zimage_lora_3000") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Kazumi character LoRA for Z-Image Turbo and full model

- Prompt
- -
Model description
Kazumi Z-Image LoRA (Turbo + Full) This repo contains two LoRA files.
kazumi_zimage_turbo_lora_3000.safetensors β This LoRA is for Z-Image Turbo. It is intended for workflows that use the Turbo checkpoint (Tongyi-MAI/Z-Image-Turbo) with 4β8 steps and ModelSamplingAuraFlow.
kazumi_zimage_full_lora_3000.safetensors β This LoRA is for the full Z-Image model. It is intended for workflows that use the full Z-Image checkpoint (Tongyi-MAI/Z-Image) with 30β40 steps, without AuraFlow. Trigger word: kazumi. Suggested strength: 0.8β1.0 depending on the scene.
Trigger words
You should use kazumi to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for boyarkinn/kazumi_zimage_lora_3000
Base model
Tongyi-MAI/Z-Image-Turbo