상세 정보
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v3.8
v1.06 - Normal LoRA, extension not required
v1.04 - Normal LoRA, extension not required
v2.19
Colored Skin - LoHa

Colored Skin - LoHa

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#애니메이션
#개념
#푸른 피부
#red skin
#colored skin
#하얀 피부
#yellow skin
#퍼플 스킨
#pink skin
#주황색 피부
#Green Skin
#검은 피부
#애니메이션
#1boy
#1girl
#푸른 피부
#red skin
#colored skin
#하얀 피부
#yellow skin
#퍼플 스킨
#pink skin
#주황색 피부
#Green Skin
#검은 피부

Please check out my Ko-Fi page if you are interested in supporting me.

LoRA commissions open! -> Fiverr

This is a LoHa LoRA! You need the extension! Why? They do a lot better with multi-concepts.

Trigger words for V3.08 (play with LoRa and tag weights!):

positive: <lora:ColoredSkinv309:0.7>(purple skin, woman)

Colors you can try are "blue skin", "green skin", "gray skin", "orange skin", "pink skin", "purple skin", "red skin", "white skin", "yellow skin", "black skin".
Experiment with adding "very dark" before the skin color tag to get darker shades of that color.
Also, I tested it for a little bit and it seems like it does still recognize colors not present in the dataset for example: "maroon skin" made a very nice red-brown color in a friend model.

Follow the steps in the Model Version notes to reproduce my images.

Sample images generated with AbyssOrangeMix3A1.

All negative embeds should be easy to find. and Prompts should be included in the sample images! Click the little icon in the bottom right to see it.

You might want to add some negatives to counter color bleeding if necessary, for example:
(purple background, purple eyes, purple clothes, purple hair)

It was trained on 200 512x512 images(20 for each color) scraped from the internet and 6 epochs using Animefull-final-pruned for the Training Model.

Danbooru tags generated by Waifu Diffusion 1.4 Tagger and fine tuned for specific details like ??????? texture, see-through, and impossible shirt or form fitting.

번역문 보기

평점 및 리뷰

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P
공고
2023-03-30
모델 게시
2023-07-04
모델 정보 업데이트
모델 상세정보
유형
LoCon
게시 날짜
2023-07-04
기본 모델
SD 1.5
버전 소개

Generate using a weight of 0.4-1.0 like this: <lora:ColoredSkinv308:0.75>.

Using improved dataset and new training settings.


How I archived my generations:

  1. txt2img: DPM++ SDE Karras with 20 steps, 512x512(can go up to 768 for wide or tall), Restore faces on (using CodeFormer weight 1.0 in Settings), Hires-fix on, to 1024x1024 (double original size) with your preferred upscaler and Denoise 0.4, CFG 7. Then send to img2img!

  2. img2img: DPM++ SED Karras with 20 steps, Restore faces on (CodeFormer weight 1), rescale to 1536x1536, CFG 7, Denoise between 0.3-0.7 (based on how much you want to improve the image), SAME PROMPT! Send to extras when happy with img2img/inpaint results.

  3. extras: Scale to x3 (final will be 4608x4608, I suggest going lower, I did x3 just for the samples here) Upscaler 1 - FatalAnime 4x, Upscaler 2 - SwinIR 4x with 0.10 visibility, GFPGAN 0.10 visibility, CodeFormer 0.10 visibility.

If anyone is curious about my version names: v{version}.{trainingEpochs}

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모델 출처: civitai

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