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# Akashi Junko (Blue Archive)
赤司ジュンコ (ブルーアーカイブ) / 아카시 준코 (블루 아카이브) / 赤司淳子 (碧蓝档案)
[**Download here.**](https://huggingface.co./khanon/lora-training/blob/main/junko/chara-junko-v1c.safetensors)
## Table of Contents
- [Preview](#preview)
- [Usage](#usage)
- [Training](#training)
- [Revisions](#revisions)
## Preview
## Usage
Use any or all of the following tags to summon Junko: `junko, slit pupils, demon horns, halo, twintails, hair ribbon, pointy ears, demon wings`
- You can also use `low wings` if the wings appear too high.
For her normal outfit: `military uniform, short sleeves, black shirt, plaid skirt, red necktie, thigh strap, black boots`
For her New Year alt: `japanese clothes, yellow kimono, black hakama skirt, black boots, kinchaku`
For her normal expression: `closed mouth, smile, :3`
- You may need to prefix the colon with a backslash character.
For her hangry expression: `open mouth, wavy mouth, skin fang, (tearing up, crying with eyes open:0.5)`
- The AI is very aggressive about drawing tears/crying. You may need to reduce the emphasis.
## Training
*Exact parameters are provided in the accompanying JSON files.*
- Trained on a set of 140 images.
- 131 normal images (9 repeats)
- 9 "multiple views" images (6 repeats)
- These were reduced because the AI was generating too many "multiple views" images.
- 3 batch size, 4 epochs
- `(131 * 9 + 9 * 6) / 3 * 4` = 1644 steps
- 0.0749 loss
- Initially tagged with WD1.4 swin-v2 model. Tags pruned/edited for consistency.
- `constant_with_warmup` scheduler
- 1.5e-5 text encoder LR
- 1.5e-4 unet LR
- 1e-5 optimizer LR
- Used network_dimension 128 (same as usual) / network alpha 128 (default)
- Resized to 32 after training
- Training resolution 768x768.
- Reduced from 832x832. Junko doesn't really have many very fine details that benefit from the higher resolution, and I think training at 832x832 may negatively impact the quality of images generated at lower resolutions.
- Trained without VAE.
- [Dataset can be found on the mega.co.nz repository.](https://mega.nz/folder/SnQDnCRD#ruLvChZGf2vQtWJN87Qs0Q)
## Revisions
- v1c (2023-02-15)
- Initial release.
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