Sign In

Nissan Skyline RS Turbo Super

21

100

9

7

Updated: Jun 17, 2025

vehicle

Verified:

SafeTensor

Type

LoRA

Stats

100

9

3

Reviews

Published

Jun 17, 2025

Base Model

Illustrious

Training

Steps: 1,500
Epochs: 10

Usage Tips

Clip Skip: 1
Strength: 0.8

Trigger Words

skyline_super_silhouette

Hash

AutoV2
C91D725E1F
Holiday 2024: Golden Donor
2018cfh's Avatar

2018cfh

Created on Civitai

Model Card: Skyline Super Silhouette Visual LoRA

Model Purpose:

This LoRA is designed to generate or stylize images of the Nissan Skyline Super Silhouette race car with high visual fidelity and authentic historic detailing. It supports creative exploration, retro motorsport illustration, and dataset generation across varied contexts and art styles.

Trigger Word(s):

skyline_super_silhouette

Use Cases:

- Automotive art and concept rendering

- Historical motorsport recreations

- Style transfer for retro racing liveries

- Dataset augmentation for detection, classification, or fine-tuning

Training Focus:

- Accurate body proportions of the Nissan Skyline Super Silhouette

- Key design elements such as box flares, widebody stance, vented hood, and oversized rear wing

- TOMICA livery, white decals, and sponsor logos

- Variety of visual elements including gold or white mesh wheels, exposed roll cage, racing seats

- Angles: side, front, rear, and three-quarter views under clean lighting

Supported Tags:

- Color and styling (e.g., red body, black aero kit, white decals)

- Race-specific components (e.g., widebody fenders, racing number, vented hood, mesh wheels)

- Visual context (studio photo, garage, showroom, racetrack, urban or outdoor settings)

- Lighting and quality descriptors (early morning light, ambient lighting, soft shadows)

Image Types:

Studio photography, exhibition photos, outdoor captures, and museum or pit garage settings

Recommended Sampling Settings:

- Strength: 0.6–0.8 for balanced fidelity and integration

- Resolution: 512x512 or higher

- Works best with SDXL Illustrious or realism-focused base models