Członkostwo PixAI
PixAI
PixAI
Generate
Sign in
Strona główna
Generowanie
Modele
Studio
NEW
Konkurs
Utwórz z Mio.2
Skrzynka narzędziowa
NEW
Guide

User LoRA

XL

SeaArt Quality Tags

#Furry
Narzędzia AI
  • Generator anime AI
  • Generator figurek anime
  • Generator kart postaci
  • Generator okładek magazynów
  • Generator pluszaków
  • Generator gigantycznych posągów

Odkrywaj

  • Popularne tagi
  • Ranking
  • Rynek Modeli
  • Konkurs
  • Aktualności

O nas

  • Guide
  • Jak używać PixAI
  • Tsubaki.2
  • Poznaj Mio
  • Zasady treści

Cennik i pomoc

  • Członkostwo
  • Pakiety kredytów
  • Kontakt

Aplikacja mobilna

  • Pobierz aplikację PixAI
  • App Store
  • Google Play
© 2026 PixAI
  • Regulamin
  • Polityka prywatności
  • Polityka praw autorskich
  • Attributions
  • Ustawa o Określonych Transakcjach Handlowych
SeaArt Quality Tags - AI Model cover image
Przesłano
14 sie 2024, 12:18
Użycia
7.6k
Opinie
Doskonały  (2)
Słowa kluczowe

best quality

Uprawnienia
  • Allow image generation & sharing
  • Zezwól użytkownikom pobierać Twój model
  • Zastosowania komercyjne

Recommended LoRAs

瑠璃垣るり - AI Model cover image

User LoRA

瑠璃垣るり
28
Honda Sora (Lonely Girl Ni Sakaraenai) [Illustrious] - AI Model cover image

User LoRA

Honda Sora (Lonely Girl Ni Sakaraenai) [Illustrious]
0
Diane Foxington XL - AI Model cover image

User LoRA

Diane Foxington XL
36
Karlach (Baldur's Gate 3) [Illustrious] Character Lora - AI Model cover image

User LoRA

Karlach (Baldur's Gate 3) [Illustrious] Character Lora
7

Opis

https://civitai.com/models/625794

SeaArt Quality Tags adds two quality tags to SeaArt Furry XL, replacing the existing best quality and worst quality. It is an SDXL successor to my Fluffyrock Quality Tags with an improved dataset and a bit of preference optimization.

Usage Just two tags this time. You can play around with weighting and tag order to control the strength.

Positive: best quality Negative: worst quality

Model Info The goal of this LoRA is to improve the style of the SeaArt Furry XL model without using any other style tags. It produces a colorful, cartoony style with thick lines but can do semi-realism if you bully it hard enough.

Improvements include:

Training an aesthetic scoring model to curate a dataset based on my preferences.

Balancing the dataset so it isn't dominated by a few prolific artists.

Manual validation every epoch to stop training when the style stops improving. Just 2 epochs was enough (20k steps).

Implement MaPO preference optimization to improve the style even after conventional training stagnated.

Good compatibility with Compassmix and Bananastrike that preserves their natural language capability. The style is less cartoony but still aesthetically pleasing.

Limitations Complicated scenes have more anatomy/coherence problems. This is actually a problem with the base model, but I wasn't able to improve it even with preference optimization.

I used a synthetic dataset for preference optimization (for each real image, I generate a "rejected" version with the same caption). This lets me build a dataset quickly, but doesn't capture the same nuances as real preference data.

MaPO is finnicky and starts to produce stippling and gridlike artifacts when training goes too long, even though the style was still improving. You might get faint artifacts in rare cases, despite my best efforts.

Komentarze