z-image-turbo loras
Collection
9 items β’ Updated
LoRA adapter trained for the concept/style "windy_storm".
Use this token in your prompt:
windy_storm*.safetensors β LoRA weightsconfig.yaml β training configurationlog.txt β training log.safetensors file into your LoRA folder.windy_storm, portrait photo, natural light, high detail(Adjust LoRA strength to taste, e.g. 0.6β1.0.)
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained(
"Tongyi-MAI/Z-Image-Turbo",
torch_dtype=torch.bfloat16
).to("cuda")
# Replace with your actual repo + filename on the Hub:
pipe.load_lora_weights("<YOUR_REPO_ID>", weight_name="<YOUR_LORA_FILENAME>.safetensors")
prompt = "windy_storm, portrait photo, natural light, high detail"
image = pipe(prompt).images[0]
image.save("out.png")
Base model
Tongyi-MAI/Z-Image-Turbo