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("jbern3812947/Space-Image-ZIT-LoRA")
prompt = "-"
image = pipe(prompt).images[0]Space Image ZIT LoRA
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Model description
Attempt at producing space images (although base ZIT does fairly well).
Recommended LoRA strength <= 0.9
Optional trigger word: Sp11
I recommend using simple terms like: galaxy, nebula, cosmic dust, stars
Trained on 32 Hubble (and similar) images.
Credit to ESA/Hubble for the images used in the dataset (CC BY 4.0).
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Tongyi-MAI/Z-Image-Turbo