initial commit

.gitattributes

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.gitignore

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+**/dataset/

README.md

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+---
+license: mit
+---

atsuko/README.md

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+# Hakari Atsuko (Blue Archive)
+
+Note: her mask was not included in the training data. Stable Diffusion can't deal with them and a mixture of mask/no-mask Atsuko would fuck things up.
+
+## Usage
+Use any or all of these tags to summon Atsuko:
+`1girl, halo, red eyes, pink hair, low twin braids`
+Her hair is sometimes tagged pink, sometimes purple, even on Danbooru.
+
+For her Arius outfit:
+`hood, white dress, hair bow, black gloves, white kneehighs, frilled legwear`
+
+For her leotard, just remove `white dress` and add `leotard` or `one-piece swimsuit` (WD unfortunately tagged it as a swimsuit more often than not).
+
+The AI likes giving her fairly prominent lips/lipstick for some reason despite her mouth being basically just a line in most of the training data.  It feels a little excessive so I just neg-prompt `lips` and it looks closer to correct.
+
+You can add or ignore `atsuko, blue archive`; while they were in her captions, their effects aren't especially strong.
+
+Weights from 0.9 - 1.2 work well depending on variant and model.
+
+Variants:
+- v3 -- 3 epochs, faster learning rate; slightly underfit but less likely to appear overcooked
+- v5 -- 4 epochs, tweaked dataset, slower learning rate; does a great job with her outfit and halo but occasionally looks overcooked
+- v6 -- v3 with v5's dataset; largely a wash, different but not necessarily better or worse.
+Pick whichever, it doesn't really matter too much.  Each one seems to have the chance of being the best for a given prompt so it's all RNG.
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+- Trained on a set of 60 images initially provided by an /hdg/ anon, I pruned/added a few here and there.
+  - Dataset included a mixture of SFW and NSFW.
+- Dataset was tagged with WD1.4 interrogator.  Shuffling was enabled.
+  - `atsuko, blue archive` were added to the start of each caption.  keep_tokens=2 was set to prevent shuffling those tokens.
+- Three variations with different training params, check the JSON files if you care.

atsuko/lora_character_atsuko-v3_57i10r_768_batch3_2e-5_3epoch.json

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+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/atsuko",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "6969",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "2e-5",
+  "unet_lr": "2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "atsuko-v3-NAI-VAE-768px"
+}

atsuko/lora_character_atsuko-v4_57i11r_768_batch3_1e-5_3epoch.json

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+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/atsuko",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "6969",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "2e-5",
+  "unet_lr": "2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "atsuko-v4-NAI-VAE-768px"
+}

atsuko/lora_character_atsuko-v4_60i11r_768_batch3_1e-5_3epoch.json

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+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/atsuko",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "6969",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1e-5",
+  "unet_lr": "1e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "atsuko-v4-NAI-VAE-768px"
+}

atsuko/lora_character_atsuko-v5_60i10r_768_batch3_1e-5_4epoch.json

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+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/atsuko",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "4",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "6969",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1e-5",
+  "unet_lr": "1e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "atsuko-v5-NAI-VAE-768px"
+}

atsuko/lora_character_atsuko-v6_60i10r_768_batch3_2e-5_3epoch.json

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+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/atsuko",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "6969",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "2e-5",
+  "unet_lr": "2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "atsuko-v6-NAI-VAE-768px"
+}

atsuko/lora_character_atsuko_57i10r_768_batch3_slower3epoch.json

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+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/atsuko",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1.2e-5",
+  "unet_lr": "1.2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "atsuko-NAI-VAE-768px"
+}

chise/README.md

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+# Waraku Chise (Blue Archive)
+Came out pretty well I think.  Smaller dataset than Mari, but otherwise very similar settings.
+
+## Usage
+Use any or all of these tags to summon Chise:
+`chise, halo, red eyes, blue hair`
+Hair and eyes are mostly optional if you describe a bit of her outfit as well.
+She naturally likes to make her `:o` expression because most art features her doing that.  However I also included images tagged with other expressions.
+Use `open mouth`, `closed mouth`, and `parted lips` as necessary to get her to make whatever expressions you want.
+
+For her normal outfit (add as many as necessary):
+`braid, japanese clothes, detached sleeves, obi, tabi, geta, sailor collar, blue bow`
+Her shoes are weird but they're tagged `geta` and the socks as `tabi`.
+
+For her swimsuit outfit (add as many as necessary):
+`side ponytail, swimsuit, striped bikini, see-through, sailor collar, side-tie bikini bottom`
+You can also add `pointed ears`, which are usually only visible in her swimsuit outfit.
+
+Weight 1 works fine. Also included epoch 6 in case you find the last epoch to be a bit stubborn with her outfits.
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+- Trained on a set of 119 images split by outfit, repeated 10 times (swimsuit) or 14 times (uniform) for 7 epochs (119 images * 10 or 14 repeats / 3 batch size * 7 epochs = 3178 steps)
+  - Dataset included a mixture of SFW and NSFW.
+- Initially tagged with WD1.4 VITv2 model, then performed heavy pruning and editing.
+  - Pruned implicit (`oni horns`) or redundant tags and simplified outfits so that they were always tagged with the same handful of tags
+  - Made sure important traits were present and consitently described, and traits like `halo` were consistent with actual visibility
+  - Added many facial expression, camera angle, and image composition hints
+- Used network_dimension 128 (same as usual) and network_alpha 64 (new)
+  - This relies on the new alpha 
+- Trained without VAE.

chise/lora_chara_chise_v1_119i13r_832_batch3_5e-5text_2e-4unet_7epoch.json

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+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/chise",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/lora/trained/chara/chise",
+  "max_resolution": "832,832",
+  "learning_rate": "",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "7",
+  "save_every_n_epochs": "2",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latents": true,
+  "caption_extension": "",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "5e-5",
+  "unet_lr": "2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "chise-v1-NoVAE",
+  "model_list": "",
+  "max_token_length": "150",
+  "max_train_epochs": "",
+  "max_data_loader_n_workers": "",
+  "network_alpha": 64,
+  "training_comment": ""
+}

hibiki/README.md

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+# Nekozuka Hibiki (Blue Archive)
+
+## Usage
+*Important:* This is a fairly temperamental LoRA due to the dataset, and it needs some wrangling to get good results.  It won't look good with vanilla NAI and the standard NAI negative prompt, despite being trained on nai-animefull-final.
+- Use a strong negative prompt.  Consider using the bad_prompt_v2 embed at a reduced strength to dramatically improve things, though it does affect the style somewhat.
+- Use a strong model.  AbyssOrangeMix2 and nutmegmix work well with this LoRA.
+- Use the negative prompt liberally to suppress cheerleader Hibiki if you don't want her, otherwise her traits tend to take over.
+
+To summon Hibiki, use the following tags.  Adjust strength as needed.
+  - `1girl, halo, black hair, blue eyes, bright pupils, animal ears, dog girl, tail, hair bobbles, goggles, eyewear on head, medium breasts`
+
+For regular Hibiki, add the following tags.  Adjust strength as needed.
+  - Prompt: `(black camisole, jacket, black shorts:1.2), (fishnet legwear:1.1)`
+  - Negative prompt: `(midriff, navel, skin tight, tight:1.4), (tattoo, arm tattoo, star sticker:1.30), ski goggles, wavy mouth, embarrassed`
+    - Cheerleader Hibiki tends to have a permanent embarrassed/wavy mouth expression unless you use negative tags to get rid of it.
+
+For cheerleader Hibiki, add the following tags.
+  - Prompt: `cheerleader, midriff, embarrassed, wavy mouth, crop top, white pleated skirt`
+  - Negative prompt: `fishnets`
+
+You can add or ignore `hibiki, blue archive`; while they were in her captions, they don't have an especially strong effect.
+
+Adjust the weight as needed.  Weights from 0.95 up to 1.25 work well (higher weights may summon Cheerleader Hibiki unintentionally).
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+- Trained on 119 images, separated into two sets.
+  - Hibiki (regular) -- 54 images, 10 repeats
+  - Hibiki (cheerleader) -- 65 images, 6 repeats
+  - Dataset included a mixture of SFW and NSFW.  Mostly SFW.
+  - As you can guess, her cheerleader alt makes up the vast majority of her art, and artists are more consistent when drawing her. Training them all together did not work well, so I had to split up the datasets.
+- Dataset was tagged with WD1.4 interrogator.  Shuffling was enabled.
+  - `hibiki, blue archive` were added to the start of each caption.  keep_tokens=2 was set to prevent shuffling those tokens.
+  - Her cheerleader outfit is much more easily recognized by the tagger, leading to stronger tags.  Even human artists can't seem to agree on what she's wearing in her normal outfit.
+- Trained at 768px resolution.  I stopped training a 512 variant because it was almost always worse and added to training time.
+- Two variants included.
+  - v1: first attempt at splitting the dataset.  Works well, but not as coherent in some ways (halo particularly) and still tends to blend details from her two outfits.
+  - v2: using the split dataset. Increased batch size slightly (3 >>> 4), reduced learning rate (3e-5 >>> 1e-5), increased epochs (1 >>> 3).  Generally an improvement, though sometimes v1 is easier to wrangle.

hibiki/lora_character_hibiki_119img9repeat_512.json

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+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hibiki",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "512,512",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "3e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hibiki-NAI-VAE-512px-357steps"
+}

hibiki/lora_character_hibiki_119img9repeat_768.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hibiki",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "3e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hibiki-NAI-VAE-768px-357steps"
+}

hibiki/lora_character_hibiki_split_65i6r-54i10r_768.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hibiki",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "3e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hibiki-v2-NAI-VAE-768px-6.10split-310steps"
+}

hibiki/lora_character_hibiki_split_65i6r-54i10r_768_batch4_slower3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hibiki",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 4,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1e-5",
+  "unet_lr": "1e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hibiki-v3-NAI-VAE-768px-6.10split-310steps-batch4-slower"
+}

hibiki/lora_character_hibiki_split_65i6r-54i10r_768_batch5_slower4epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hibiki",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 5,
+  "epoch": "4",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1e-5",
+  "unet_lr": "1e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hibiki-v3-NAI-VAE-768px-6.10split-310steps-batch5-slower-4epoch"
+}

hina/README.md

@@ -0,0 +1,26 @@
+# Sorasaki Hina (Blue Archive)
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+- Trained on 106 images curated by anon on /hdg/, repeated 10 times (1060 total images / 3 batchsize = ~354 iterations)
+  - Dataset included a mixture of SFW and NSFW 
+  - Dataset included a lot of her swimsuit alt outfit, so it has a bit of a harder time producing her standard outfit (the military uniform)
+  - It does better with her more casual outfit ("sleeveless shirt, miniskirt") and obviously very well with her school swimsuit
+- Dataset was tagged with WD1.4 interrogator.  Shuffling was enabled.
+  - `hina, blue archive` were added to the start of each caption.  keep_tokens=2 was set to prevent shuffling those tokens.
+- Two resolution variants included (512px, 768px)
+  - The 768px version seems just generally better to my eyes but not overwhelmingly.  They're definitely quite different so I've kept both.
+
+## Usage
+Hina needs a few tags to be summoned reliably.  Some common tags in her dataset:
+`1girl, halo, parted bangs, demon horns, long hair, white hair, purple eyes, low wings, small breasts`
+
+You can add or ignore `hina, blue archive`; while they were in her captions, they don't seem to be particularly strong for some reason.
+
+You can use the 512px or 768px variants.  I want to say the 768px one is better, but it's hard to say definitively.  Give both a shot and post your findings.
+
+Weight 0.85-1.05 should work well depending on model.
+
+## Dataset
+Dataset curated by anon on /hdg/: https://mega.nz/folder/ayhWjJDA#xDGSB3T-yRnK6aRajsJ05g
+/h/thread/7101537

hina/lora_character_hina_106img10repeat_512.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hina",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "512,512",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "3e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hina-NAI-VAE-512px-354steps"
+}

hina/lora_character_hina_106img10repeat_768.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hina",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "3e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hina-NAI-VAE-noreg-768-10reps"
+}

hina/lora_character_hina_106img8repeat_512.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hina",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "512,512",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "3e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hina-NAI-VAE-noreg-512"
+}

hina/lora_character_hina_106img8repeat_768.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hina",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "3e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hina-NAI-VAE-noreg-768"
+}

hina/lora_character_hina_106img9repeat_512.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hina",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "512,512",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "3e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hina-NAI-VAE-noreg-512-moresteps"
+}

hina/lora_character_hina_106img9repeat_768.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/hina",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "3e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "hina-NAI-VAE-noreg-768-moresteps"
+}

iroha/README.md

@@ -0,0 +1,28 @@
+# Natsume Iroha (Blue Archive)
+
+## Usage
+Use any or all of these tags to summon Iroha:
+`1girl, halo, red hair, very long hair, wavy hair, grey eyes, small breasts`
+
+For her normal outfit:
+`peacked cap, open jacket, collared shirt, partially unbuttoned, red necktie, armband, sleeves past wrists`
+
+You can add or ignore `iroha, blue archive`; while they were in her captions, their effects aren't especially strong.
+
+The network seems simultaneously undertrained and overfitted in some ways so weights are kind of all over the place, just play around with them. 0.8-1.2 work alright.
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+- Trained on 95 images using a modified dataset curated by anon on /hdg/, repeated 7 times (665 total images / 3 batchsize  = ~222 iterations per epoch, 3 epochs)
+  - Dataset included a mixture of SFW and NSFW
+- Sightly increased learning rate from the last few (1e-5 >>> 1.5e-5)
+- Seems a bit underfitted at times, overfitted others.
+  - Frequently forgets her jacket/shirt colors despite them being a very consistent part of her outfit, and her halo is pretty incoherent.
+  - She really likes doing a particular kind of toothy smirk that was too common in her dataset. When you don't want it, discourage it with `closed mouth` and negative `open mouth`.
+- Dataset was tagged with WD1.4 interrogator.  Shuffling was enabled.
+  - `iroha, blue archive` were added to the start of each caption.  keep_tokens=2 was set to prevent shuffling those tokens.
+- No variants. I trained 8 iterations of this LoRA and they all had issues of some kind, this latest one is the best of them.
+
+## Dataset
+Dataset curated by anon on /hdg/: https://mega.nz/folder/Hqg10AAI#9xsrFmuA8oqVBlhsj95y6w
+/h/thread/7104198

iroha/lora_character_iroha_95i7r_768_batch3_slower3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/iroha",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1e-5",
+  "unet_lr": "1e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "iroha-v1-NAI-VAE-768px"
+}

iroha/lora_character_iroha_95i8r_768_batch3_slower3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/iroha",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1e-5",
+  "unet_lr": "1e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "iroha-v2.2-NAI-VAE-768px"
+}

iroha/lora_character_iroha_95i9r_768_batch3_slower3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/iroha",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "1234",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1e-5",
+  "unet_lr": "1e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "iroha-v3-NAI-VAE-768px"
+}

iroha/lora_character_iroha_95i9r_768_batch4_slower3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/iroha",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 4,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "1234",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1e-5",
+  "unet_lr": "1e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "iroha-v3.1-NAI-VAE-768px"
+}

iroha/lora_character_irohav5_95i7r_768_batch3_midlr_3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/iroha",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1.5e-5",
+  "unet_lr": "1.5e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "iroha-v5-NAI-VAE-768px"
+}

iroha/lora_character_irohav5mod_95i7r_768_batch3_midlr_3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/iroha",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1.5e-5",
+  "unet_lr": "1.5e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "iroha-v5-mod-NAI-VAE-768px"
+}

izuna/README.md

@@ -0,0 +1,29 @@
+# Kuda Izuna (Blue Archive)
+
+## Usage
+Use any or all of these tags to summon Izuna:
+`1girl, halo, yellow eyes, brown hair, animal ears, fox girl, fox tail, fox hair ornament, bangs, medium breasts, red eyeshadow`
+
+For her normal outfit:
+`blue sailor collar, red neckerchief, partially fingerless gloves, ninja, floral print, fishnets, single thighhigh`
+
+For her swimsuit outfit:
+`striped bikini, denim shorts, visor cap, highleg bikini, red neckerchief`
+
+You can add or ignore `izuna, blue archive`; while they were in her captions, their effects aren't especially strong.
+
+Weight 0.90-1.2 should work well depending on model.
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+- Trained on 67 images curated by anon on /hdg/, repeated 10 times (670 total images / 3 batchsize  = ~223 iterations per epoch)
+  - Dataset included a mixture of SFW and NSFW
+  - Dataset included a lot of her swimsuit alt outfit but it seems to be able to produce her normal outfit readily.
+- Reduced learning rate (3e-5 >>> 1e-5) and increased epochs (1 >>> 3).  I'll likely do this from now on since it seems to produce more consistent results.
+- Dataset was tagged with WD1.4 interrogator.  Shuffling was enabled.
+  - `izuna, blue archive` were added to the start of each caption.  keep_tokens=2 was set to prevent shuffling those tokens.
+- No variants, she was a good girl.
+
+## Dataset
+Dataset curated by anon on /hdg/: https://mega.nz/folder/Hqg10AAI#9xsrFmuA8oqVBlhsj95y6w
+/h/thread/7104198

izuna/lora_character_izuna_67i10r_768_batch3_slower3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/izuna",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1e-5",
+  "unet_lr": "1e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "izuna-v1-NAI-VAE-768px"
+}

kagura-nana/README.md

@@ -0,0 +1,29 @@
+# Kagura Nana, alt outfit (Virtual Youtuber)
+Request for anon on /hdg/.  Sorta rough, not much art for her and especially NSFW art.
+
+## Usage
+
+Tags: `1girl, cat ears, tail, two side up, two-tone hair, blue eyes, small breasts`
+
+Outfit: `sleeveless dress, off shoulder, jacket, choker, neck bell, striped bow, skirt`
+
+The original version of this was extremely overfit due to bad training data, and was highly resistant towards nudity because there was literally none of it in the dataset. I did some pruning, generated/found a couple of nude images, and cleaned up tags -- now her outfit is manually tagged and exclusively described using the tags above so it is generally more composable (ie. you can prompt for the `jacket` but negative prompt the `sleeveless dress` and it will work fairly reliably). I included `skirt` in images where the flared, ruffled bottom of her dress was visible even though it's not really a skirt but it may help with outfit composition.
+
+It's still slightly overtrained so turning down the weights a bit (0.85 - 1) is recommended.
+
+Three variations:
+- v1: the original, in the `old` folder.  Not really recommended unless you want it to hyperfocus on her details and outfit at the cost of NSFW capability. Might be okay for mixing?
+- v3: new cleaned up dataset, somewhat overcooked
+- v4: same as v3 with reduced steps, except for the small number of NSFW images which were boosted
+
+I did something different with this one and tagged the four lewd images in her dataset with `nsfw`.  I can't really tell if it helped or hurt, but you may as well prompt for that if you want porn.
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+- Trained on a set of 67 images initially provided by an /hdg/ anon, heavily curated and re-tagged.
+  - Dataset included a mixture of SFW and NSFW.
+  - Some NSFW images were outputs from v1 of the model. Does not appear to have caused down syndrome Nanas from model inbreeding.
+- Dataset was initially tagged with WD1.4 interrogator and then heavily pruned and manually cleaned up.
+  - `kagura nana, virtual youtuber` were added to the start of each caption.  keep_tokens=2 was set to prevent shuffling those tokens.
+  - All ambiguities or alternate tags for her outfit were removed and replaced with the standard set above.  Prompt for `sleeveless dress` not `sleeveless shirt`, and `jacket` not `black jacket` for the highest correlation. 
+- Three variations with different training params, check the JSON files if you care.

kagura-nana/lora_character_altnana-_105i20r_768_midlr_cosine.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/kagura-nana",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1.5e-5",
+  "unet_lr": "1.5e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "nana-v1-NAI-VAE-768px"
+}

kagura-nana/lora_character_nana-v2_65i20r_768_midlr_cosine.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/kagura-nana",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1.5e-5",
+  "unet_lr": "1.5e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "nana-v2-NAI-VAE-768px"
+}

kagura-nana/lora_character_nana-v3_65i20r_768_midlr_cosine-2e-5.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/kagura-nana",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "1",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "2e-5",
+  "unet_lr": "2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "nana-v3-NAI-VAE-768px"
+}

kagura-nana/lora_character_nana-v4_split-61.7r-4.10r_768_cosine-1.5e-5.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/kagura-nana",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1.5e-5",
+  "unet_lr": "1.5e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "nana-v4-NAI-VAE-768px"
+}

koharu/README.md

@@ -0,0 +1,60 @@
+# Shimoe Koharu (Blue Archive)
+
+Changed training methodology around for Koharu. It took way more time and effort due to the degree of manual tagging involved, but it turned out pretty well.
+
+I'll probably return to this one later to make further improvements now that I've got a much better handle on the impact of tagging and how to get the most out of larger datasets.  I don't expect to manual tag every future student, though.
+
+## Usage
+Use any or all of these tags to summon Koharu:
+`koharu, 1girl, halo, pink eyes, ringed eyes, head wings, low wings, pink hair`
+Unlike previous LoRAs, the character's name does help this one somewhat.  You can probably omit her hair to save tokens.
+
+The vertical line running down her body appears consistently, but may not always reach past her chest because artists are inconsistent in how they draw it.  You can try to describe it literally: "vertical black line running past navel" or whatever.  Don't try `tattoo` unless you want womb tattoos.
+
+It does a decent, but not perfect job with her eyes. Adding some combination of `embarrassed`, `open mouth`, `swirly eyes` with varying degrees of emphasis can draw out her characteristic horny retard look.
+
+I tried to add the slit pupils expression and the model sorta gets it, but not very well.  You can prompt it with `slit pupils` and `flustered` but it generally creates abominations.
+
+For her normal Trinity outfit:
+`school uniform, off shoulder, hat, skirt`
+
+Some of her swimsuits are in there too.
+
+Weights from 0.8 - 1.05 should work well.
+
+### Important
+This LoRA may be more aggressive than others in forcing a close-up/portrait camera.  I believe this is because I scraped Booru tags for this one, and WD1.4 more reliably tags camera angles and image composition than human taggers.  You can mitigate this by always prompting for an angle or composition tag, like `above waist` or `cowboy shot` or `from above`.  You can combine them, too.
+
+Trying to prompt Koharu from behind or the side generally doesn't work very well -- it can render her back if you use `from behind` and `back focus`, but her wings will be attached to her stomach and her halo will be flipped,because the AI doesn't know how to generalize those traits to different angles and there's not enough training data for them.
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+
+Koharu's training was handled substantially differently.
+
+- Trained on a heavily curated set of 183 images, most repeated 6 times. 1150 total steps.
+  - Dataset included a mixture of SFW and NSFW.
+  - Doubled the number of steps because the dataset was larger than usual.  I typically target 450 - 650.
+- New tagging methodology.  No WD1.4 tags; instead I scraped tags from Sankaku Complex using Hydrus and manually cleaned them up.
+  - Removed tons of shit tags
+  - Made sure important traits were present and consitently described, and traits like `halo` were consistent with actual visibility
+  - Pruned lots of redundant tags and simplified outfits.  There is no `black serafuku, long sleeves`, only Koharu's `school uniform`.
+  - Added camera angles and image composition hints
+  - Added facial expressions (particularly `embarrassed`) and unusual pupils when present
+- Different learning rate than usual.
+  - 5e-5 text encoder (typically 1e-5 ~ 2e-5)
+  - 2e-4 UNet (typically one order of magnitude faster than text)
+  - This was experimental -- human tags tend to be more varied, allowing for more expressiveness (WD1.4 did not do a good job with her) but potentially requiring more training. The dataset was also larger.
+- VAE removed. I usually train the dataset on the NAI VAE but after some tests, I think this was leading to oversaturated outputs and it does not play nicely with alternative VAEs.
+  - May offer a No VAE and a WD1.4 VAE in the future as these seem to present the best results across many configurations
+  
+While I think the experimental things I tried out with this dataset worked out well enough to be called a success, tag cleanup took literal hours and I will probably not be able to put nearly so much effort into every character. I just really like Koharu.  I will probably retrain some old ones with at least the new hyperparameter methodologies, though.
+
+## To-do
+- More consistently tag NSFW/SFW/nudity
+- Add more image composition/camera angle tags
+- Find additional images with prominent swirly eyes
+- Improve tags for socks/shoes
+- Remove `halo` tag from images where it is just barely visible to force camera to pull further away
+- Un-fuck wings from side angle (folded wings tag?)
+- Add `looking away` / `facing away` to applicable images because it is impossible 

koharu/lora_character_koharu_v1_158i5r_768_batch3_5e-5text_1.5e-4unet_3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/koharu",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "5e-5",
+  "unet_lr": "1.5e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "koharu-v1-NoVAE"
+}

koharu/lora_character_koharu_v2_180i6r-split_832_batch3_5e-5text_2e-4unet_3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/koharu",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "832,832",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "5e-5",
+  "unet_lr": "2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "koharu-v2-NoVAE"
+}

kokona/README.md

@@ -0,0 +1,28 @@
+# Sunohara Kokona (Blue Archive)
+
+## Usage
+Use any or all of these tags to summon Kokona:
+`1girl, halo, animal ears, orange eyes, long hair, grey hair`
+She really doesn't need many, just `1girl, halo` is enough to summon an instantly recognizable version of her.  The model may be a little overtrained but it looks good.
+
+For her normal outfit:
+`china dress, vertical-striped dress, white skirt, frilled skirt, off-shoulder, jacket`
+
+Somewhat frequently, a strange, mysterious man in a black suit likes to appear out-of-frame beside her.  You can shoo him away with `1boy` in the negative prompt.  Not sure why this happens as there was nothing like it in the training data.
+
+The AI is generally pretty good at picturing her, but it really struggles with her pout.  Try various combinations of `pout`, `:t`, `pouting` and negative prompt `wavy mouth` to try to get it to appear correctly, or just use img2img without the LoRA.  It seems to be related to the LoRA since vanilla NAI can do pouting just fine.
+
+Her stamp is in the training data and it sorta knows what it is but is probably too small to be recognized by the AI.
+
+You can add or ignore `kokona, blue archive`; while they were in her captions, their effects aren't especially strong.
+
+Weights close to 1 work well with her, she's very cooperative.
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+- Trained on 95 curated images, repeated 7 times (665 total images / 3 batchsize  = ~222 iterations per epoch, 3 epochs)
+  - Dataset included a mixture of SFW and NSFW.
+- 1.5e-5 learning rate, same as Iroha.
+- Dataset was tagged with WD1.4 interrogator.  Shuffling was enabled.
+  - `kokona, blue archive` were added to the start of each caption.  keep_tokens=2 was set to prevent shuffling those tokens.
+- No variants, she's well-behaved.

kokona/lora_character_kokona_95i7r_768_batch3_midlr_3epoch.json

@@ -0,0 +1,43 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/kokona",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "lr_scheduler": "constant_with_warmup",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "3",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latent": true,
+  "caption_extention": ".txt",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "1.5e-5",
+  "unet_lr": "1.5e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "kokona-NAI-VAE-768px"
+}

mari/README.md

@@ -0,0 +1,50 @@
+# Iochi Mari (Blue Archive)
+I used a bigger dataset than normal since Mari has a lot of good art (253 images).
+
+This was a tricky LoRA to train since she has two very distinct outfits (and her gym outfit has as much art without her jacket as with). The LoRA recalls both outfits, and even her swimsuit, but you may need to negative prompt elements of whichever outfit you don't want.
+
+## Usage
+Use any or all of these tags to summon Mari:
+`mari, halo, 1girl, blue eyes`
+`cat ears` was only tagged on images where her cowl was not present, in which case `animal ear headwear` is the tag you want.
+Hair and eyes are optional.
+
+For her normal outfit (you don't usually need all of these):
+`single braid, animal ear headwear, nun, habit, puffy long sleeves, blue neckerchief, white sailor collar`
+Her shoes were tagged `mary janes`.
+The sleeves of her outfit leak into other outfits/nudity so you may need to negative prompt them (`puffy long sleeves`)
+
+For her gym uniform outfit (you don't usually need all of these):
+`low ponytail, sportswear, track jacket, shorts, gym shirt, ponytail, id card, bottle`
+Images with her jacket visible were tagged `track jacket`. If the jacket was open, I added `open jacket`.
+Images with her gym shirt visible (so not those where her jacket was closed) were tagged `gym shirt`.  Adding `white` can help.
+`wet, wet clothes` was common in the trianing data and works well.
+
+For her swimsuit (only a handful of images in the training data, so use emphasis):
+`black one-piece swimsuit, frilled swimsuit, frills, paw print`
+Negative prompt: `competition swimsuit`
+
+Included three epochs.  I did way more steps than normal in pursuit of perfect halo gens, 
+- epoch 7 (3542 steps) = nails her expressions and outfits pretty well but outfit details can leak over. best halo but still not great
+- epoch 6 (~3000 steps) = pretty good balance between the others
+- epoch 4 (~2000 steps) = less overfit on outfits but halo and expression consistency is not as good
+
+Weight 1 works fine for the most part.  Epoch 7 may be somewhat stubborn/overfit on some parts of her outfit, in which case you may have better luck dropping down to epoch 6 or 4.
+
+
+## Training
+*All parameters are provided in the accompanying JSON files.*
+- Trained on a set of 253 images repeated 6 times, 7 epochs (253 images * 6 repeats / 3 batch size * 7 epochs = 3542 steps)
+  - Dataset included a mixture of SFW and NSFW.
+  - Same params as Koharu, but with almost double the amount of steps, since the dataset was large and I wasn't initially satisfied with halo/facial expression consistency
+- Initially tagged with WD1.4, then performed heavy pruning and editing.
+  - Pruned redundant tags and simplified outfits so that they were always tagged with the same handful of tags
+  - Made sure important traits were present and consitently described, and traits like `halo` were consistent with actual visibility
+  - Added many facial expression, camera angle, and image composition hints
+- Made a hard-coded tweak to bmaltais's LoRA GUI script.
+  - Previously increasing the `resolution` values (512 >> 768 >> 832) would not increase `max_bucket_reso`, so buckets were limited to 1024 (the default) in either dimension.
+  - Per the kohya_ss README, when increasing `resolution` to 768, it is recommended to increase `max_bucket_reso` to 1280 to keep the bucket aspect ratios the same as 512 resolution
+  - I adjusted the script to set `max_bucket_reso` based on `resolution`, using the formula:
+    - `max_bucket_reso = resolution * (1 + (512 / resolution))` which causes bucket aspect ratios to be the same as 512 for any given resolution.
+  - In practice, this only affected a very small number of very tall or very wide images so I don't think it would have made much of a difference
+- Trained without VAE.

mari/lora_character_mari_v1_253i8r_832_batch3_5e-5text_2e-4unet_4epoch.json

@@ -0,0 +1,48 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/mari",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "832,832",
+  "learning_rate": "",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "6",
+  "save_every_n_epochs": "2",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latents": true,
+  "caption_extension": "",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "5e-5",
+  "unet_lr": "2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "mari-v3-NoVAE",
+  "model_list": "",
+  "max_token_length": "150",
+  "max_train_epochs": "",
+  "max_data_loader_n_workers": ""
+}

mari/lora_character_mari_v2_253i6r_768-fixed-max-bucket-reso_batch4_5e-5text_5e-4unet_4epoch.json

@@ -0,0 +1,48 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/mari",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "768,768",
+  "learning_rate": "",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 4,
+  "epoch": "5",
+  "save_every_n_epochs": "1",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latents": true,
+  "caption_extension": "",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "5e-5",
+  "unet_lr": "5e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "mari-v2-NoVAE",
+  "model_list": "",
+  "max_token_length": "150",
+  "max_train_epochs": "",
+  "max_data_loader_n_workers": ""
+}

mari/lora_character_mari_v3_253i8r_832_batch3_5e-5text_3e-4unet_4epoch.json

@@ -0,0 +1,48 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/mari",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "832,832",
+  "learning_rate": "",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "4",
+  "save_every_n_epochs": "3",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "23",
+  "num_cpu_threads_per_process": 32,
+  "cache_latents": true,
+  "caption_extension": "",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "5e-5",
+  "unet_lr": "3e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "mari-v3-NoVAE",
+  "model_list": "",
+  "max_token_length": "150",
+  "max_train_epochs": "",
+  "max_data_loader_n_workers": ""
+}

mari/lora_character_mari_v4_253i6r_832_batch3_5e-5text_2e-4unet_6epoch.json

@@ -0,0 +1,48 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/mari",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "832,832",
+  "learning_rate": "",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "6",
+  "save_every_n_epochs": "2",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latents": true,
+  "caption_extension": "",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "5e-5",
+  "unet_lr": "2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "mari-v4-NoVAE",
+  "model_list": "",
+  "max_token_length": "150",
+  "max_train_epochs": "",
+  "max_data_loader_n_workers": ""
+}

mari/lora_character_mari_v4_253i6r_832_batch3_5e-5text_2e-4unet_7epoch.json

@@ -0,0 +1,48 @@
+{
+  "pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
+  "v2": false,
+  "v_parameterization": false,
+  "logging_dir": "",
+  "train_data_dir": "G:/sd/training/datasets/mari",
+  "reg_data_dir": "G:/sd/training/datasets/regempty",
+  "output_dir": "G:/sd/repo/extensions/sd-webui-additional-networks/models/lora",
+  "max_resolution": "832,832",
+  "learning_rate": "",
+  "lr_scheduler": "cosine_with_restarts",
+  "lr_warmup": "5",
+  "train_batch_size": 3,
+  "epoch": "7",
+  "save_every_n_epochs": "2",
+  "mixed_precision": "fp16",
+  "save_precision": "fp16",
+  "seed": "31337",
+  "num_cpu_threads_per_process": 32,
+  "cache_latents": true,
+  "caption_extension": "",
+  "enable_bucket": true,
+  "gradient_checkpointing": false,
+  "full_fp16": false,
+  "no_token_padding": false,
+  "stop_text_encoder_training": 0,
+  "use_8bit_adam": true,
+  "xformers": true,
+  "save_model_as": "safetensors",
+  "shuffle_caption": true,
+  "save_state": false,
+  "resume": "",
+  "prior_loss_weight": 1.0,
+  "text_encoder_lr": "5e-5",
+  "unet_lr": "2e-4",
+  "network_dim": 128,
+  "lora_network_weights": "",
+  "color_aug": false,
+  "flip_aug": false,
+  "clip_skip": 2,
+  "gradient_accumulation_steps": 1.0,
+  "mem_eff_attn": false,
+  "output_name": "mari-v4-NoVAE",
+  "model_list": "",
+  "max_token_length": "150",
+  "max_train_epochs": "",
+  "max_data_loader_n_workers": ""
+}