Hassaku aims to be a anime model with a bright and distinct anime style. 
You can run Hassaku XL and use its API on SinkIn: https://sinkin.ai/m/JWknjgr
My Discord for everything related to anime models and art.
If you'd like to support my work, you can do so at: SubscribeStar, every bit helps and is truly appreciated!
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Supporters:
Thanks to my supporters tamashiicolle, pttcot, SETI and Kodokuna
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Using the model:
- The model is trained using images with minimal disruptive elements such as floating text, logos, speech bubbles, and signatures. If any of these elements are present in an image, please include the prompt "signature" as a negative prompt 
- Metadata and franchise tags are excluded—please do not use them. Tags such as "highres" and franchise-related tags like "re:zero kara hajimeru isekai seikatsu" are not used in training 
- A CFG of 3 to 7 is recommended 
- Look at the example images, to see how the model should be used 
- Model is trained to be not complicated in use, tag order: 
 First are the number of person, then character names, rest.
 Example: 1girl, rem \(re:zero\), standing, masterpiece, upper body
- NoobAIs Loras working for the most part better in compare to Illustrious loras 
- Here are some resolution options for SDXL: - 1536 x 640 
- 1344 x 768 
- 1216 x 832 
- 1152 x 896 
- 1024 x 1024 
- 896 x 1152 
- 832 x 1216 (most recommended) 
- 768 x 1344 
- 640 x 1536 
 
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Version and License info:
- Below V1 merges ANIMAGINE XL 3.0 
- Version V1 use Illustrious-XL & WAI-NSFW-illustrious-SDXL with additional training 
- V2 is trained on its own and don't include any extra merge. Base was V1, it is trained to include newer or missing characters. It was also used for further training tests 
- V3 is a merge of Illustrious-XL and V2.2, to fix some issues and was also trained to include newer or missing characters - All Models using the Fair AI Public License 1.0-SD license. 
Description
It is simply a continuation of training with a extended dataset.
With many diffent styles, eyes getting a bit unprecise, testing it only for training check. I can fix that, but i spend that time better on further training and dataset working, instead staying and spending time on a between Version.