moki shota

画师moki画风示例图随便搞的，我还是更喜欢搞NSFW关于体型的描述只需要”plump“即可，无需”fat“等提示词，剩下的提示词和生成普通的正太的一致关于不可描述的部位有专门进行优化训练，效果算是我的模型中最好的一个训练参数眼睛和脚还是有点问题的，脚的话...那位画师好像不太爱画model_train_type = "sdxl-lora" pretrained_model_name_or_path = "./sd-models/0208-000147.safetensors" vae = "./sd-models/vae/sdxl_vae.safetensors" train_data_dir = "./train/moki" prior_loss_weight = 1 resolution = "1280,1280" enable_bucket = true min_bucket_reso = 256 max_bucket_reso = 1080 bucket_reso_steps = 32 bucket_no_upscale = true output_name = "moki" output_dir = "/root/autodl-tmp/output" save_model_as = "safetensors" save_precision = "bf16" save_every_n_epochs = 1 save_state = false max_train_epochs = 30 train_batch_size = 12 gradient_checkpointing = true gradient_accumulation_steps = 1 network_train_unet_only = true network_train_text_encoder_only = false learning_rate = 0.0001 unet_lr = 0.0001 text_encoder_lr = 0.00001 lr_scheduler = "cosine_with_restarts" lr_warmup_steps = 0 lr_scheduler_num_cycles = 0 optimizer_type = "AdamW" network_module = "networks.lora" network_dim = 64 network_alpha = 32 log_with = "tensorboard" logging_dir = "./logs" caption_extension = ".txt" shuffle_caption = false keep_tokens = 3 max_token_length = 255 noise_offset = 0.1 color_aug = false flip_aug = false seed = 1337 mixed_precision = "bf16" full_bf16 = true xformers = true lowram = false cache_latents = true cache_latents_to_disk = true仅供参考

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