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# Igusa Haruka (Blue Archive) |
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伊草ハルカ (ブルーアーカイブ) / 이구사 하루카 (블루 아카이브) / 伊草春香 (碧蓝档案) |
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[**Download here.**](https://huggingface.co/khanon/lora-training/blob/main/haruka/chara-haruka-v1c.safetensors) |
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## Table of Contents |
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- [Preview](#preview) |
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- [Usage](#usage) |
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- [Training](#training) |
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- [Revisions](#revisions) |
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## Preview |
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![Haruka preview 1](example-001-v1b.png) |
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![Haruka preview 2](example-002-v1b.png) |
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![Haruka preview 3](example-003-v1b.png) |
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## Usage |
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Use any or all of the following tags to summon Haruka: `haruka, 1girl, halo, short hair with long locks, purple eyes` |
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For her normal outfit: `school uniform, hairclip, purple jacket, collared shirt, juliet sleeves, belt, miniskirt, black skirt, boots` |
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- The AI is slightly stubborn with Haruka's normal outfit, likely because she doesn't have much art that does not feature long sleeves of some sort. |
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- To remove her jacket sleeves, prompt `sleeveless` and use `long sleeves` in the negative prompt. |
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- To remove the purple bowtie/tie clip, prompt `collarbone` and use `bowtie` in the negative prompt. |
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For her nervous/creepy smile: `nervous smile, nervous, sweat, wavy mouth, [closed mouth:parted lips:0.75]` |
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- Use `sanpaku, constricted pupils, crazy eyes, yandere` or similar for more intense expressions. |
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[Here is a list of all tags including in the training dataset, sorted by frequency.](all_tags.txt) |
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## Training |
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*Exact parameters are provided in the accompanying JSON files.* |
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- Trained on a set of 143 images. |
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- 138 without "multiple views" (9 repeats) |
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- 5 "multiple views" (4 repeats) |
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- 3 batch size, 4 epochs |
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- `(138 * 9 + 5 * 4) / 3 * 4` = 1683 steps |
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- 0.083 loss |
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- Initially tagged with WD1.4 swin-v2 model. Tags pruned/edited for consistency. |
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- [Tagging methodology detailed here.](tagging%20methodology.md) |
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- `constant_with_warmup` scheduler |
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- 1.5e-5 text encoder LR |
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- 1.5e-4 unet LR |
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- 1e-5 optimizer LR |
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- Used network_dimension 128 (same as usual) / network alpha 128 (default) |
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- Resized to 32 after training |
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- Training resolution 832x832. |
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- Trained without VAE. |
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## Revisions |
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- v1b (2023-02-23) |
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- Initial release. |
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