详情
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v4.0
v3.3
v3.2
v3.1
Husbando LoCon

Husbando LoCon

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145
412
#動畫
#性感
#????
#同性戀
#?????
#bara
#肖像
#guy
#handsome
#風格
#yaoi
#插圖
#??????
#男性
#男士
#男人
#肖像
#husbando
#男孩們
#動畫
#Boy
#混沌
#????
#同性戀
#?????
#bara
#風格
#yaoi
#插圖
#??????
#男性
#男士
#locon

It takes substantial time and efforts to bake models. If you appreciate my models, I would be grateful if you could support me on Ko-fi ☕ .

Husbando LoCon is a LyCORIS for creating bara/yaoi ?????? and ???????? ?????????? males.

🚀 Please also check out Selai Mix, my recent checkpoint merge model release, if you love the aesthetics of Husbando LoCon!

Features

  • Easy to create good-looking masculine characters using tag-based prompts.

  • Good male genitalia.

  • Good solo / solo focus homoerotic content.

  • Bara/yaoi ?????? depicting 2 or more people are highly erroneous. You'll need luck and careful prompting to get things right.

Recommended Settings (v4)

  • CLIP skip: 2

  • You can start by trying a weight of 0.5 with CFG scale 7.

  • For ?????? art, I recommend LoRA weight of 1.0 with CFG scale 9.

  • Since Selai Mix already contains Husbando LoCon v4.0, a lighter weight such as 0.3 should already give you the desired effect. You should not set the weight to over 0.7 when using on Selai Mix.

How to use

  • Select any checkpoint that works with tag-based prompts. Recommended models: Selai Mix and AnyLoRA.

  • Select a VAE if the checkpoint model you're using doesn't have a baked-in VAE, or else you'll find your generated images have dull colors. Recommended VAEs: blessed2, vae-ft-mse-840000-ema-pruned or kl-f8-anime2.

  • Make sure to follow the steps in How to use a LoRA.

  • Generate at 512 base resolution (512x768, 512x512 or 768x512) and use hires fix to improve the details. Recommended upscaler: R-ESRGAN 4x+ Anime6B; denoising strength: 0.4.

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avatar
Koolchh
48
363
公告
2023-03-20
发布模型
2023-11-30
更新模型資訊
模型详情
類型
LoCon
发布時間
2023-11-30
基础模型
SD 1.5
版本介绍
  • Fixed the overfitting problem in previous versions.

  • Even larger training dataset (6,617 images)

  • Auto tagged with wd-v1-4-moat-tagger-v2 with zero pruning.

  • Used flip augmentation and color augmentation.

  • Used multi resolution noise during training.

  • Obtained from LoCon extraction after fine-tuning the entire model.

  • Downscaled the LoCon dimension to 128.

许可范围
來源: civitai

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