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grimoire/release_notes/v1.0.md
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A LoRA based on 4267 [Grimoire A: Private Grimoire Magic Academy](https://grimoire.applibot.co.jp/) cards, recognizing 60+ characters to varying degrees.
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A request by Civit user themonky007. The model is far from complete but there
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Lesson of the day: suitable learning rates can differ significantly between datasets (this uses 2e-4 while the Idolmaster models use 1e-3).
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## Training info
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Dataset:
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* [4267 Grimoire cards](https://huggingface.co/datasets/gustproof/sd-data/blob/main/grimoire_cards_notext_denoised.zip) extracted from [official](https://play.google.com/store/apps/details?id=jp.co.applibot.
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Tags generated with [SmilingWolf/wd-v1-4-convnextv2-tagger-v2](https://huggingface.co/SmilingWolf/wd-v1-4-convnextv2-tagger-v2) with a threshold of 0.35. No balancing and tag cleaning. Images were processed with [RealESRGAN_x4plus_anime_6B](https://github.com/xinntao/Real-ESRGAN/blob/master/docs/anime_model.md).
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A LoRA based on 4267 [Grimoire A: Private Grimoire Magic Academy](https://grimoire.applibot.co.jp/) cards, recognizing 60+ characters to varying degrees.
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A request by Civit user themonky007. The model is far from complete but there are currently no plans to further improve it. [The dataset](https://huggingface.co/datasets/gustproof/sd-data/blob/main/grimoire_cards_notext_denoised.zip) is available for those willing to take on the task.
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Lesson of the day: suitable learning rates can differ significantly between datasets (this uses 2e-4 while the Idolmaster models use 1e-3).
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## Training info
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Dataset:
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* [4267 Grimoire cards](https://huggingface.co/datasets/gustproof/sd-data/blob/main/grimoire_cards_notext_denoised.zip) extracted from [official](https://play.google.com/store/apps/details?id=jp.co.applibot.grimoireOfflineLily.android) [offline](https://play.google.com/store/apps/details?id=jp.co.applibot.grimoireOfflineRose.android) [apps](https://play.google.com/store/apps/details?id=jp.co.applibot.grimoireOfflineSunflower.android) with text removed (characters labeled by themonky007)
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Tags generated with [SmilingWolf/wd-v1-4-convnextv2-tagger-v2](https://huggingface.co/SmilingWolf/wd-v1-4-convnextv2-tagger-v2) with a threshold of 0.35. No balancing and tag cleaning. Images were processed with [RealESRGAN_x4plus_anime_6B](https://github.com/xinntao/Real-ESRGAN/blob/master/docs/anime_model.md).
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