Detalhes
Recomendado
NAIXL-E1-vpred06-dim32
PonyXL-D1-AdamW8bit-e32
LyCORIS-GEM

LyCORIS-GEM

1
0
94
#Estilo
#Illustrious

An experimental LoCon trained on outputs from my MIX-GEM-T2_2 model (and a few other MIX-GEM outputs to make up the gap). I spent a lot of time finetuning that model to my ideal aesthetic and I'd rather try to retrieve the style directly from the model than try to remix on a new SDXL base from scratch. Outputs are not very clean and this LoCon has a lot of issues. I will likely have to regenerate the dataset a couple of times with cleaner outputs. Likely there will be a lot of versions of hits LoCon, this will be an iterative process with a lot of rebakes.

Insights gleaned from prototyping:

  • Prodigy is worse than AdamW8bit at training style LoCons on PonyXL, even at a higher learning rate it retains a lot less than AdamW8bit. But it also destroys the base model's posing a lot faster, whereas the prodigy tends to keep a lot better with the original posing.

  • LoCons are better at training for styles than LoRAs.

  • Style retention comes hand in hand with magnifying small mistakes. This isn't a huge issue with ordinary style training, but is extremely problematic when training on SD1.5 outputs because of the way that unnecessary noise gets diffused into random elements which don't really makes aesthetic sense. Case has to be put into selecting only clean outputs.

Things to try in the future:

  • White background regularization images

  • Hiding hands as much as possible

  • Using copyright characters as part of the dataset

After testing, for some reason this LoCon works poorly on autismMixSDXL which washes out a lot of the details, but works extremely well on 4th tail.

Ver tradução

Classificação e Avaliação

5.0 /5
0 classificação(ções)

Sem classificações ou avaliações suficientes

no-data
Sem dados
avatar
Jemnite
458
8.1K
Conversar com o modelo
Anúncio
2024-02-21
Publicar Modelo
2025-01-11
Atualizar info do modelo
Detalhes do modelo
Tipo
LoCon
Tempo de Publicação
2025-01-11
Modelo básico
Illustrious
Introdução à Versão

Quick and dirty attention layer extract from MIX-GEM-XL checkpoint. conv dim 32, network dim 16, baseline checkpoint is NAIXL vpred06.

Escopo da licença
Fonte: civitai

1. Os direitos dos modelos repostados pertencem aos criadores originais.

2. Criadores originais que desejam reivindicar seus modelos devem contatar a equipe do SeaArt AI pelos canais oficiais. Clique para reivindicar

Escopo da licença de criação
Transmissão ao vivo
Fusão
Permitir download
Licença comercial
Imagens geradas podem ser vendidas ou usadas para fins comerciais
Permitir revenda de modelos ou sua venda após a combinação
QR Code
Baixar App SeaArt
Continue sua jornada de criação com IA no celular