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Mint_NTE_Outfit1

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bf16 SafeTensor

MINT_NTE_Outfit1_anima.safetensors

BF16, good balance • 33.14 MB

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Type
LoRA
Stats

71

78

44

Generation

Loaded

Reviews
Published

Oct 11, 2026

Base Model

Anima

Training
Steps: 1,500
Hash
AutoV2
831E247029
Trigger Words
mint \(nte\), cat girl, cat ears, animal ear fluff, long hair, multicolored hair,streaked hair, aqua hair, braid, cat tail, pink eyes, large breasts
black gloves, hairband, (cat face on hairband:0.8), white over shirt, black dress, black corset, black skirt, white thighhighs,thigh strap, black boots, fanny belt pouch, gold aiguillette
default creator card background decoration
Followers - 1684

1.7K

Downloads - 137087

137.1K

Generations - 306990

307K

License:

Anima

The Anima Model is licensed by CircleStone Labs LLC. Copyright CircleStone Labs LLC. IN NO EVENT SHALL CIRCLESTONE LABS LLC BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.

Built on NVIDIA Cosmos

17c02773-1eae-45b9-98d2-bfe45e5588a8-2.jpg

Single-Outfit Support

This model is trained only on Mint's default outfit.

Single costume training captured complex clothing details better than multi-costume training.

If you're looking for the multi-outfit version, check the below 👇

https://civitai.com/models/2996298/mintnte3outfits


Quick Reference

LoRA Weight: 0.8 – 1.0

Character Trigger:

mint \(nte\), cat girl, cat ears, animal ear fluff, long hair, multicolored hair,streaked hair, aqua hair, braid, cat tail, pink eyes, large breasts

Outfit1: Default

black gloves, hairband, (cat face on hairband:0.8), white over shirt, black dress, black corset, black skirt, white thighhighs,thigh strap, black boots, fanny belt pouch, gold aiguillette

Managed to land on an art style right between 3D and the official art.

Feel free to add "3D" to the NP if you prefer.


My reserch

Outfit1 Key Points A and B

single outfit models outperformed 3outfits models.

As a side effect, having too much 3D source data caused the output style to look more like 3D.


Comparing Anima and IL

There is no difference between them.

Surprisingly, Anima performed just as well as IL even though the text encoder wasn't a perfect match.

Turns out, as long as the dataset quality is solid, training just the U-Net is more than enough.