Instructions to use liming518/ZITflatchets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use liming518/ZITflatchets 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("liming518/ZITflatchets") prompt = "young latino woman wearing a bikini" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/img1.jpg
text: young latino woman wearing a bikini
- output:
url: images/img2.jpg
text: young latino woman wearing a tight top
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: null
lora from civitai

- Prompt
- young latino woman wearing a bikini

- Prompt
- young latino woman wearing a tight top