If you only want to imitate the artstyle and don't particularly care about portraying a Yadokari ship girl, I highly recommend using v6 instead.
Trained on AOM2-nutmegmixGav2. Compared to v6-AOM2-nnmGav2, the model now more closely imitates details of the underlying dataset. This means it will both reproduce character traits more accurately, but also it will tend to crush background details (most the training set is simple background) and can more easily ignore prompts (see the attached UNet/TEnc grid).
Example Images
Made using AOM2-nutmegmixGav2 txt2img LoRA weight of about 0.5, then upscaling with Ultimate SD Upscale and no further processing. Image grids are txt2img only.
If you only want to imitate the artstyle and don't particularly care about portraying a Yadokari ship girl, I highly recommend using v6 instead.
Trained on AOM2-nutmegmixGav2. Compared to v6-AOM2-nnmGav2, the model now more closely imitates details of the underlying dataset. This means it will both reproduce character traits more accurately, but also it will tend to crush background details (most the training set is simple background) and can more easily ignore prompts (see the attached UNet/TEnc grid).
Example Images
Made using AOM2-nutmegmixGav2 txt2img LoRA weight of about 0.5, then upscaling with Ultimate SD Upscale and no further processing. Image grids are txt2img only.
Negative prompts utilizes bad-artist and bad-artist-anime embeddings from https://huggingface.co/NiXXerHATTER59/bad-artist as well as the bad-hands-5 embedding from https://huggingface.co/yesyeahvh/bad-hands-5/tree/main
Hiryuu image uses a non-public LoRA.
Training Parameters
"net_dim": 128,
"alpha": 128.0,
"scheduler": "cosine_with_restarts",
"cosine_restarts": 3,
"warmup_lr_ratio": 0,
"learning_rate": 0.0001,
"text_encoder_lr": 5e-05,
"unet_lr": 0.0001,
"shuffle_captions": true,
"keep_tokens": 5,
"train_resolution": 768,
"lora_model_for_resume": null,
"unet_only": false,
"text_only": false,
"vae": null,