description: <h2 id="heading-56">About</h2><p>Character: Inuyama Aoi (Yurucamp)</p><p></p><h2 id="heading-31">Update History</h2><h3 id="heading-32">2023-12-05</h3><p>Add v3.<br />Detail: Read "About this version"</p>
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modelVersions.description: <p>inuko v3</p><p>prompts</p><pre><code>inuyama_aoi, mediam_hair, breasts, bangs, brown_hair, hair_ornament,, side_ponytail, swept_bangs, thick_eyebrows, hair_bobbles, skin_fang, green eyes , fang, sailor_collar,, sweater, , school uniform, yellow sweater,  , serafuku, pleated skirt, checkered clothes, white_neckerchief
  </code></pre><p># sd -scripts command</p><p>Generate command : <a target="_blank" rel="ugc" href="https://github.com/RedRayz/Kohya_lora_param_gui">RedRayz/Kohya_lora_param_gui: GUI for kohya-ss sd-scripts (</a><a target="_blank" rel="ugc" href="http://github.com">github.com</a><a target="_blank" rel="ugc" href="https://github.com/RedRayz/Kohya_lora_param_gui">)</a></p><ul><li><p><strong>LoRA-C3Lier (</strong>conv2d)</p></li><li><p>pagedAdamW8bit</p></li><li><p>Dim64 , Alpha32</p></li><li><p>CUT: IN07-08, OUT10-11</p></li></ul><pre><code>accelerate launch --num_cpu_threads_per_process 4 train_network.py --pretrained_model_name_or_path "C:\ProgramTools\__GenerativeAI\StableDiffusionModels\nai.ckpt" --train_data_dir "H:\Resources\Resources_AI\forLeaningImages\Yurucamp\inuyama_aoi\v2" --output_dir "H:\Resources\Resources_AI\__Models\__Lola\__MyLoRAs" --network_module "networks.lora" --network_args "conv_dim=64" "conv_alpha=32"  "down_lr_weight=1,1,1,1,1,1,1,0,0,1,1,1" "mid_lr_weight=1" "up_lr_weight=1,1,1,1,1,1,1,1,1,1,0,0" --xformers --persistent_data_loader_workers --cache_latents --max_token_length 225 --max_data_loader_n_workers 1 --enable_bucket --save_model_as "safetensors" --lr_scheduler_num_cycles 4 --mixed_precision "fp16" --learning_rate=1e-04 --text_encoder_lr=5e-05 --resolution 768 --train_batch_size 2 --max_train_epochs 12 --network_dim 64 --network_alpha 32 --shuffle_caption --keep_tokens 1 --save_every_n_epochs 1 --optimizer_type "PagedAdamW8bit" --lr_warmup_steps 200 --output_name "lora_yurucamp_inuyama_aoi_v3_pagedAdamW8bit_d64a32_NP5" --clip_skip 2 --save_precision "fp16" --lr_scheduler "cosine" --min_bucket_reso 320 --max_bucket_reso 1536 --caption_extension ".txt" --seed 42 --logging_dir "E:\Creative\Program\Github\__AI\Art\TraningLog\sd_scripts\log" --training_comment "lora_yurucamp_inuyama_aoi_v3_pagedAdamW8bit_d64a32_NP5" --sample_every_n_steps=537 --sample_prompts="H:\Resources\Resources_AI\forLeaningImages\__SamplePrompts\sample_prompts_basic1girl_inuko.txt" --sample_sampler=euler --log_prefix=inuko_v3</code></pre><p># Extract only the necessary layers</p><p>Tools: SuperMerger</p><p>enable only IN02_IN04_OUT03-06</p><ol><li><p>set to lbwpreset.txt</p></li></ol><pre><code>CHARA:0,0,1,1,0,0,0,0,1,1,1,1,0,0,0,0,0</code></pre><ol><li><p>Enter text "LoRA_name:1:CHARA"</p></li><li><p>Merge LoRA</p></li><li><p>Done</p></li></ol><p># Additional information</p><p>I think you can get the same result even if you only learn IN02_IN04_OUT03-06 at the time of training.</p>
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modelVersions.description: <p></p><p>▼Tagger</p><pre><code>python tag_images_by_wd14_tagger.py --batch_size 5 "H:\\Resources\\Resources_AI\\forLeaningImages\\Yurucamp\\inuyama_aoi\\40_inuyamaaoi 1girl"
  </code></pre><p></p><p>▼Leaning</p><p>64images * 40=2560</p><p>4epoch = 10240</p><p></p><p>dim4, 768解像度、4エポック、</p><p></p><p><code>accelerate launch --num_cpu_threads_per_process 24 train_network.py --pretrained_model_name_or_path=C:/ProgramTools/__GenerativeAI/StableDiffusion_AUTOMATIC1111_v6.0/stable-diffusion-webui/models/Stable-diffusion/nai_sfw.ckpt --train_data_dir=H:\\Resources\\Resources_AI\\forLeaningImages\\Yurucamp\\inuyama_aoi --reg_data_dir=H:\\Resources\\Resources_AI\\forLeaningImages\\touka\\10images --output_dir=H:\\Resources\\Resources_AI\\__Models\\__MyTrainModels --train_batch_size=2 --use_8bit_adam --xformers --mixed_precision=fp16 --save_every_n_epochs=1 --save_model_as=safetensors --seed=42 --network_module=networks.lora --enable_bucket --color_aug --max_token_length=225 --text_encoder_lr 5e-5 --network_dim=4 --clip_skip=2 --learning_rate=1e-4 --max_train_steps=10240 --resolution=768,768</code></p><p></p>
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modelVersions.name: Yurucamp_InuyamaAoi_v1
modelVersions.publishedAt: 2023-02-06T16:14:30.561Z
name: Yurucamp_InuyamaAoi
tags: anime character yurucamp girls