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README.md
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# Charater from Honkai impact
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## Elysia
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### Brief intro
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LORA of Elysia, with
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### Training dataset
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#### Default costume/Miss Pink Elf
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*
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* 30 normal 360 3D model snapshots
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#### Default herrscher costume/herrscher of human:ego
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*
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*
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#### Miad costume
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*
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* 30 normal 360 3D model snapshots
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#### swimsuit
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*
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* 60 normal 360 3D model snapshots
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In addition, I have also included
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### Captioning
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### Training setup
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Trained with Kohya_SS stable diffusion trainer Base model was [Anything V3.0 full](https://huggingface.co/Linaqruf/anything-v3.0/blob/main/anything-v3-fp32-pruned.safetensors) Trainig process consist of two phases. The first one with default parameters of:
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*
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*
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### Result
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# Charater from Honkai impact
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## Elysia/爱莉希雅-V2
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### Brief intro
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LORA of Elysia, with 5 costumes in game. civitAI page [Download](https://civitai.com/models/14616)
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### Training dataset
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#### Default costume/Miss Pink Elf
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75 images in total, in folder "14_Elysia (miss pink elf) 1girl"
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* 45 normal illustrations, non-nude
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* 30 normal 360 3D model snapshots
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#### Default herrscher costume/herrscher of human:ego
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129 images in total, in folder "11_elysia (herrscher of humanego) 1girl"
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* 39 normal illustrations, included few NSFW, not completely nude though
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* 90 normal 360 3D model snapshots
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#### Miad costume
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75 images in total, in folder “16_Elysia-maid 1girl”
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* 45 normal illustrations, non-nude
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* 30 normal 360 3D model snapshots
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#### swimsuit
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80 images in total, in folder “14_elysia-swimsuit 1girl”
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* 20 normal illustrations, non-nude
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* 60 normal 360 3D model snapshots
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In addition, I have also included 52 images with non-official costumes in a new folder "10_Elysia 1girl"
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### Captioning
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Captioning with WD1.4, with threshold 0.7.
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After the auto captionin is done, I added "elysia \ \(miss pink elf\ \) \ \(honkai impact\ \)", "elysia \ \(herrscher of human:ego\ \) \ \(honkai impact\ \)", "Elysia-maid", "Elysia-swimsuit" and "1girl, elysia \ \(honkai impact\ \)" to the captioning respectively as identifiers. In addition, I also manually editted the captioning to make sure that there was no overlap of prompts between each concepts.
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### Training setup
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Trained with Kohya_SS stable diffusion trainer Base model was [Anything V3.0 full](https://huggingface.co/Linaqruf/anything-v3.0/blob/main/anything-v3-fp32-pruned.safetensors) Trainig process consist of two phases. The first one with default parameters of:
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* Lion, Cosine with restarts
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* learning_rate: 0.00003
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* text_encoder_lr: 15e-6
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* unet_lr: 0.00003
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Trained for 10 epochs with upper parameters, feel underfit, thus trained another 2 epoch with 1/3 the initial LR.
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### Result
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