Instructions to use hodgy/joana with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hodgy/joana 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("hodgy/joana") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Joana โ Z-Image Turbo LoRA
An identity/character LoRA for Tongyi-MAI/Z-Image-Turbo.
Suggested trigger word
Start prompts with joana. This word is inferred from the repository and weight filename; the original training captions are not included, so the exact trigger token could not be independently verified.
Example prompt:
Photorealistic portrait of joana, natural window light, realistic skin texture, detailed eyes, 85mm photography, shallow depth of field.
Recommended settings
- Base model:
Tongyi-MAI/Z-Image-Turbo - Start with LoRA strength
0.8โ1.0. - Use 8 inference steps.
- State the desired pose, clothing, framing, lighting, and setting explicitly.
- Lower the strength if prompt flexibility decreases; raise it gradually if identity is weak.
fal.ai example
{
"prompt": "Photorealistic portrait of joana, natural window light, realistic skin texture, 85mm photography",
"image_size": "portrait_4_3",
"num_inference_steps": 8,
"loras": [
{
"path": "https://huggingface.co/hodgy/joana/resolve/main/joana_z-image-turbo_lora.safetensors",
"scale": 0.9
}
]
}
File
joana_z-image-turbo_lora.safetensorsโ Z-Image Turbo LoRA weights in Safetensors format
The file contains 480 LoRA tensors. Its embedded metadata identifies PyTorch format but does not include the training step count or captions.
Intended use and limitations
Use for character-consistent portrait and creative image generation. Results can vary with pose, distance, occlusion, stylization, and LoRA strength. Hands, text, small facial details, and crowded scenes may contain artifacts. Outputs inherit limitations and biases from the base model and training data.
Responsible use
Use only where you have the necessary rights and permission. Do not use the adapter to impersonate, deceive, defame, harass, exploit, or violate privacy or publicity rights. Clearly disclose synthetic imagery when context could cause viewers to mistake it for a real event or endorsement.
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Model tree for hodgy/joana
Base model
Tongyi-MAI/Z-Image-Turbo