README.md

metadata

base_model: Tongyi-MAI/Z-Image-Turbo
tags:
  - lora
  - text-to-image
  - diffusion
  - z-image-turbo
  - character
license: other

hardbody — LoRA

LoRA adapter trained on Tongyi-MAI/Z-Image-Turbo.

Note: trigger_word is not set in the training config. In practice, use the concept name hardbody in your prompt, and/or rely on the dataset’s default caption described below.

Base model

• Tongyi-MAI/Z-Image-Turbo

Trigger / keyword

• Suggested keyword: hardbody
• Default caption used during training: curvy female body

Files

• *.safetensors — LoRA weights
• config.yaml, job_config.json — training configuration
• (optional) log.txt — training log

How to use

A) ComfyUI / AUTOMATIC1111

1. Put the .safetensors file into your LoRA folder.
2. Prompt examples (safe / non-explicit):
   • hardbody, athletic figure, studio photo, soft lighting, high detail
   • hardbody, fashion shoot, street style, natural light, high detail

(Adjust LoRA strength to taste, e.g. 0.6–1.0.)

B) Diffusers (generic example)

import torch
from diffusers import DiffusionPipeline

pipe = DiffusionPipeline.from_pretrained(
    "Tongyi-MAI/Z-Image-Turbo",
    torch_dtype=torch.bfloat16
).to("cuda")

pipe.load_lora_weights("thorjank/<REPO_NAME>", weight_name="<YOUR_LORA_FILENAME>.safetensors")

prompt = "hardbody, athletic figure, studio photo, soft lighting, high detail"
image = pipe(prompt).images[0]
image.save("out.png")