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V2
A pretty versatile version, does most of the sizes and shapes pretty easily, prompts can be relatively simple (as seen in the examples)
I suggest using seeds2 sampler with ddim_uniform scheduler and the 8 step Turbo LoRA.

Breasts, areoles and nipples on MiniMax H3, and control over them from the prompt. Base H3 renders a chest as an approximate shape and ignores anything you say about it. This gives you size, areole size and areole color as things you type.

Trigger is HMBreasts. Lead with it.

The four axes

These aren't tags. Write them as plain English inside the sentence about her chest, the same way the model learnt them.

Breast size - tiny · small · medium · large · very large
Shape - natural · perky · round · perfectly shaped · saggy · sagging · hanging · pressed together
Areole size - tiny · small · medium · large · very large Areole colourpale · ghost · brown · dark
Nipples - erect · hard · pierced

Spelling matters here. It learnt areoles, so write it that way.

The dataset has plenty of each, but as you all know, AI is non-deterministic so don't get mad if the results you're expecting doesn't appear right away.

How the clause reads

HMBreasts, large, natural breasts, medium sized brown areoles and erect nipples

HMBreasts, small, perky breasts, tiny sized pale areoles and hard nipples

HMBreasts, very large, round breasts, large sized ghost areoles and erect nipples

Mix the axes freely. They were trained independently, so tiny breasts with large sized dark areoles is a combination it can actually give you.

What it doesn't do

• Genitals. That's HMPussy, and the two stack. This one owns the chest and nothing below it.

• Faces, bodies or identity. It's a single-concept anatomy adapter, so put it under your character or scene LoRA.

One honest limitation

medium is the weakest of the five sizes. The training material clustered at the two ends, so tiny and small steer hard, large and very large steer hard, and the middle is softer than either. If medium drifts bigger or smaller than you wanted, that's why. A shape word will usually pull it back.

It's trained on stills, so it teaches H3 what a chest looks like. How it behaves through motion still comes from the base model.