Princess attina (the little mermaid)

Princess Attina – The Little Mermaid

Summary
A LoRA of Princess Attina from Disney’s The Little Mermaid, trained to capture her iconic look — brown bun hairstyle, green eyes, crown, orange mermaid tail, and shell bikini. Perfect for generating detailed fantasy art and underwater scenes with a mix of elegance and ocean mystery.

Description
This LoRA brings to life Princess Attina, one of Ariel’s sisters from Disney’s The Little Mermaid. The model is carefully trained to capture her signature appearance — brown hair tied in a bun, bright green eyes, and a crown that highlights her royal heritage. With her distinctive orange mermaid tail, shimmering scales, and classic shell bikini, Attina embodies both elegance and the mysterious allure of the ocean.

Whether you want to recreate scenes from the underwater kingdom or explore new fantasy interpretations, this LoRA allows you to generate highly detailed and expressive images. From the sparkle of her crown to the subtle curves of her mermaid form, every element has been refined to deliver consistency and creative flexibility.

✨ This version of the LoRA was trained for Pony Diffusion V6 XL ✨

Recommended trigger words:
brown hair, bun, green eyes, crown, medium breasts, monster, mermaid, orange tail, scales, shell bikini, cleavage, belly, bare shoulders

The model works well for fantasy art, stylized character design, and underwater scenes, but can also adapt seamlessly into other artistic styles depending on your prompts.

Recommended usage

This LoRA is optimized for local / offline Stable Diffusion setups.

Best results achieved with:

• Easy Diffusion

• Automatic1111

• ComfyUI

Online generators may apply LoRA weights inconsistently or limit advanced parameters, which can negatively affect output quality.

Recommended settings:

• LoRA weight: 0.6 – 1.0 (adjust based on desired strength)

• Sampler: DPM++ 2M / DPM++ 2M Karras

• CFG Scale: 5 – 8

• Steps: 20 – 30 (can be increased or decreased depending on style, prompt complexity, and personal preference)