Kohaku-XL-gamma

Kohaku XL Gamma

A SDXL anime base model aims to create unique artworks.

<div style="display:flex; flex-direction: row; width: 100%;"> <div><img style="display:block;" src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/afc1dc39-3a1c-4db9-9942-0b2c150124ce/original=true/00946.jpeg"/></div> <div><img style="display:block;" src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/20751b43-3d91-4802-b5cb-ce3857d1027a/original=true/00937.jpeg"/></div> <div><img style="display:block;" src="https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/fade32c7-7cb8-4a69-84f3-d3da0f4b319d/original=true/00943.jpeg"/></div> </div>

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Introduction

This model can be seen as a derivative of Animagine XL 3.0 project.<br> Basically I'm collaborating with Linaqruf for making better Anime base model (and it is obvious that we have different goal/target)<br> We share our models and technique to improve our models' quality.<br> And that is also how this model been created.<br>

Base7

Kohaku-XL base7 is resumed from beta7 and use same dataset that beta series have used. But this time I use my own metadata system to create captions. (Can be taken as advanced version of what linaqruf used, will open source it soon)

Trainin details:<br> LR: 8e-6/2e-6<br> Scheduler: constant with warmup<br> Batch size: 128 (batch size 4 * grad acc 16 * gpu count 2) <br>

Gamma rev1

Kohaku-XL Gamma rev1 is a merged model which combine the learned diff from anxl3 and kohaku xl base 7. With this forumla:

gamma rev1 = beta7 + 0.8 * (anxl3 - anxl2) + 0.5 * (base7 - beta7)

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Usage

Parameter

This model is trained under 768x1024 to 1024x1024 ARB. It is recommended to use pixel count within 786432 ~ 1310720.<br> Recommended CFG scale is 4~7.<br> Sampler should not matter.<br>

Tagging

This model use my own system for quality tags or something like that. <br> So although this model combine the diff weight from anxl3, I will still recommend user to use mine (or both) tagging system.<br>

The format of prompt is as same as anxl3. (You can check the sample images I post)

Rating tags:

• General: safe
• Sensitive: sensitive
• Questionable: nsfw
• Explicit: explicit, nsfw

Quality tags (Better to worse):

• Masterpiece
• best quality
• great quality
• good quality
• normal quality
• low quality
• worst quality

Year tags (New to Old):

• newest
• recent
• mid
• early
• old

You may meet some subtle mosaic-like artifact, that may be caused by high-lr or bad resizing/image encoding.<br> I will try to fix it in next version. For now, try to use R-ESRGAN anime6b or SCUNet models for fixing it.<br>

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Future plan

Since my dataset have some resize/webp artifacts that will harm the models. I will recreate my dataset based on my new system (and opensource it once I done it).

The next plan is to train model on larger (3M-6M) dataset with better configuration (which will require A100s and I plan to spend about 2000-10000 USD on it, if you like my works, consider to sponsor me via buy-me-a-coffee or some BTC-sutff)