<h3 id="ver-anima-v1">Ver Anima V1</h3>Trained base on Anima V0.1 base with LoRA_Easy_Training_Scripts. See about this version for training details.<h3 id="introduction">Introduction</h3>A LyCORIS to enhance autopaizuri under clothes concepts. 2 triggerwords set. See the examples first.<span style="background-color:rgb(26, 27, 30);color:rgb(141, 141, 143);font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;;font-size:16px">Trained based on NOOB V-PRED EQ VAE exprimental version: <a target="_blank" rel="ugc" href="https://civarchive.com/models/1858821/noobai-v-pred-10-with-eq-vae">https://civarchive.com/models/1858821/noobai-v-pred-10-with-eq-vae</a><h3 id="pros">Pros</h3><ul><li>Concept enhancement</li></ul><h3 id="cons">Cons</h3><ul><li>Distorched limbs and genitals</li><li>Many trials needed for side view</li><li>Style influence</li></ul>

Autopaizuri under clothes enhancement

[[subsets]]caption_extension = ".txt"caption_tag_dropout_rate = 0.05image_dir = "G:/dataset/concept/autopaizuri_under_clothes/11_aplong"keep_tokens = 1name = "11"num_repeats = 11random_crop_padding_percent = 0.05shuffle_caption = true[[subsets]]caption_extension = ".txt"caption_tag_dropout_rate = 0.05image_dir = "G:/dataset/concept/autopaizuri_under_clothes/5_aphyper"keep_tokens = 1name = "5"num_repeats = 5random_crop_padding_percent = 0.05shuffle_caption = true[[subsets]]caption_extension = ".txt"caption_tag_dropout_rate = 0.05image_dir = "G:/dataset/concept/autopaizuri_under_clothes/5_aptipout"keep_tokens = 1name = "5_1790613178385557300"num_repeats = 5random_crop_padding_percent = 0.05shuffle_caption = true[[subsets]]caption_extension = ".txt"caption_tag_dropout_rate = 0.05image_dir = "G:/dataset/concept/autopaizuri_under_clothes/5_apunder"keep_tokens = 1name = "5_1790613178400564600"num_repeats = 5random_crop_padding_percent = 0.05shuffle_caption = true[train_mode]train_mode = "lora"[general_args.args]persistent_data_loader_workers = truevae_batch_size = 5pretrained_model_name_or_path = ""mixed_precision = "bf16"gradient_checkpointing = truegradient_accumulation_steps = 1seed = 42max_data_loader_n_workers = 1max_token_length = 225prior_loss_weight = 1.0sdpa = truemax_train_epochs = 20cache_latents = truecache_latents_to_disk = true[general_args.dataset_args]resolution = 1024batch_size = 5[network_args.args]network_dim = 32network_alpha = 16.0min_timestep = 0max_timestep = 1000network_train_unet_only = true[optimizer_args.args]optimizer_type = "ProdigyPlusScheduleFree"lr_scheduler = "constant"loss_type = "l2"learning_rate = 1.0unet_lr = 1.0max_grad_norm = 1.0[saving_args.args]output_dir = "G:/LoRA_Easy_Training_Scripts/output"output_name = "autopaizuri_under_clothes-anima1.0-V1-loha-dim32conv16AR0.5-NewTag"save_precision = "bf16"save_model_as = "safetensors"save_every_n_epochs = 1save_toml = truesave_toml_location = "G:/LoRA_Easy_Training_Scripts/output"[logging_args.args]log_prefix_mode = "disabled"run_name_mode = "default"[anima_args.args]pretrained_model_name_or_path = "G:/sd-webui-forge-neo/models/Stable-diffusion/ANIMA/anima_baseV10.safetensors"qwen3 = "G:/sd-webui-forge-neo/models/text_encoder/qwen_3_06b_base.safetensors"vae = "G:/sd-webui-forge-neo/models/VAE/qwen_image_vae.safetensors"qwen3_max_token_length = 512t5_max_token_length = 512timestep_sampling = "sigmoid"sigmoid_scale = 1.0[edm_loss_args.args]edm2_loss_weighting = false[bucket_args.dataset_args]enable_bucket = truemin_bucket_reso = 256max_bucket_reso = 2048bucket_reso_steps = 64[network_<a target="_blank" rel="ugc" href="http://args.args.network">args.args.network</a>_args]conv_dim = 16conv_alpha = 8.0algo = "loha"train_llm_adapter = "false"[optimizer_args.args.optimizer_args]betas = "0.95,0.99"beta3 = "None"weight_decay = "0"weight_decay_by_lr = "True"d0 = "2e-5"d_coef = "1"d_limiter = "True"schedulefree_c = "0"eps = "None"split_groups = "True"split_groups_mean = "False"factored = "True"factored_fp32 = "True"use_bias_correction = "True"use_stableadamw = "True"use_schedulefree = "True"use_speed = "False"stochastic_rounding = "True"fused_back_pass = "False"use_cautious = "False"use_grams = "False"use_adopt = "False"use_orthograd = "False"use_focus = "False"

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