Ore! Tomba! [Illustrious/Pony]

v4 Tomba characters
Fatbuns
7 months ago

A style based on the available artworks from Tomba games!

Illustrious / NTRMix

v3:

3D Tomba

As a request, I trained a lora to be specific on the 3D renders of Tomba.

Trigger words: tmb4, pink spiky hair, green shorts, barefoot, shirtless.

Use strength of 0.8 to 1

Tabby

Was a bit of a wonky tonky, as there's only one single concept art of tabby, so I had to make a simple lora of her first, then train a lora on that.. fun.

Trigger: t4bby, green hair, long hair, hair bow, red bow

Use strength of 0.7 to 1

Tomba
Use strength of 0.5 to 0.8~ 1.0 works, but it's strong.

Lora is designed around Tomba himself. Trained on character concepts from the special edition of the game + the 3d renders from earlier versions.

t0mba: Global trigger - The same-ish looks as the evil pigs in 2.1.
r3nd3r: The harsh 3d render look
p1ush: A weird and awkward "plushie" look, from the promotional render of tomba. It has big eyes. I RECOMMEND PUTTING THIS IN NEGATIVE PROMPTS

Trained on NTR MIX XIII

v2:

Trained on art from the Prima guide (found on internet archive (thanks for the reference, Atanok Si)) and the tomba 3D-ish renders. This should be better.

t0mb4 for the general trigger

tomba for the 3D-ish tomba renders.

It's trained on prompts like pig, ghost, clown, horror ghost etc.

v2.1:

Based off of the game filed for early game development - The evil pigs

3v1l for the general trigger, then use "pig, no humans", then your prompt.

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Popularity

230 ~10

Info

Base model: Illustrious
Trigger word:

Version v4 Tomba characters: 1 File

To download these files, please visit this page from a desktop computer.

About this version: v4 Tomba characters

This version is trained on ChatGPT 4O's 3d versions of the available rips + the rips I did myself.

All of them are trained with a simple background, with majority being white background.

The image uploads for the 30th, which should be the first ones uploaded by myself, are the prompts that were used for image tagging.

Training data is on the discord in the description.

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