z-image-turbo loras
Collection
9 items
•
Updated
LoRA adapter trained on Tongyi-MAI/Z-Image-Turbo.
Note:
trigger_wordis not set in the training config. In practice, use the concept namehardbodyin your prompt, and/or rely on the dataset’s default caption described below.
hardbody curvy female body*.safetensors — LoRA weightsconfig.yaml, job_config.json — training configurationlog.txt — training log.safetensors file into your LoRA folder.hardbody, athletic figure, studio photo, soft lighting, high detailhardbody, fashion shoot, street style, natural light, high detail(Adjust LoRA strength to taste, e.g. 0.6–1.0.)
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")
Base model
Tongyi-MAI/Z-Image-Turbo