Instructions to use jarod2212/LatinMan_Vogue_Zit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jarod2212/LatinMan_Vogue_Zit 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("jarod2212/LatinMan_Vogue_Zit") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Latin Man fashion Lora Zit

- Prompt
- -

- Prompt
- -

- Prompt
- -

- Prompt
- -

- Prompt
- -

- Prompt
- -

- Prompt
- -

- Prompt
- -

- Prompt
- -

- Prompt
- -

- Prompt
- -
Model description
LatinMan_Vogue_ZIT is a highly consistent male LoRA, designed to generate Vogue-style editorial portraits, with Latin aesthetics, warm skin, defined features and professional photographic rendering. It is designed for those who want: elegant male portraits fashion campaign look natural and luminous skin coherence of the face even with long hair advertising yield (warm or cold light) clean half‑body and portrait, without artifacts
This LoRA does not “invent” a different man every time: maintains identity, style and coherence, like a true professional model.
⭐ 📸 What to expect from LoRA With the latmanvg trigger word, the model produces:
coherent male faces
modern latin aesthetic
warm and uniform skin
editorial rendering by magazine
excellent response to warm and cold lights
short, medium, long, curly or tied hair without feminization
fashion outfit: blazer, unbuttoned shirt, wet tank top, bare torso (not NSFW)
zero drift, zero artifacts, zero “ethnicity change”
Works perfectly with:
portrait
half body
studio photography
advertising light
fashion editorial
⭐ 🛠️ How he was trained LatinMan_Vogue_ZIT was trained with:
original dataset created manually (no stolen images)
images generated and curated one by one
manual selection, cleaning, cropping and balancing
1250 steps → 2500 images viewed
ZIT training on SDXL compatible basis
rank and parameters calibrated for maximum consistency without rigidity
The dataset includes:
hair variations (long, short, medium, curly, tied)
light variants (warm, cold, rim light, soft light)
outfit variations (blazer, shirt, tank top, bare torso)
mood variations (editorial, advertising, cinematic)
How to use it Recommended prompt:
man, latmanvg, [hair], [outfit], [light], [editorial style] Example:
portrait, man, latmanvg, medium hair, cold advertising light, glossy skin, fashion editorial
Download model
Download them in the Files & versions tab.
- Downloads last month
- 33
Model tree for jarod2212/LatinMan_Vogue_Zit
Base model
Tongyi-MAI/Z-Image-Turbo