Upload Flat_painted_lineart_illustration_lora_v1/Flat_painted_lineart_illustration.toml with huggingface_hub
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Flat_painted_lineart_illustration_lora_v1/Flat_painted_lineart_illustration.toml
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pretrained_model_name_or_path = "sd-models/animefull-final-pruned.safetensors"
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train_data_dir = "/kaggle/input/lora-train-picture/Flat_painted_lineart_illustration"
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shuffle_caption = true
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caption_extension = ".txt"
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keep_tokens = 1
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resolution = "768,768"
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enable_bucket = true
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output_dir = "/kaggle/working/output"
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output_name = "Flat_painted_lineart_illustration"
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save_precision = "fp16"
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save_every_n_epochs = 1
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train_batch_size = 2
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max_token_length = 225
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xformers = true
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max_train_epochs = 20
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seed = 114514
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gradient_accumulation_steps = 64
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mixed_precision = "fp16"
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clip_skip = 2
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logging_dir = "/kaggle/working/output/logs"
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log_with = "wandb"
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log_prefix = "Flat_painted_lineart_illustration"
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log_tracker_name = "Flat_painted_lineart_illustration"
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noise_offset = 0.06
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lowram = true
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sample_every_n_epochs = 1
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sample_prompts = "/kaggle/input/lora-train-picture/Flat_painted_lineart_illustration/tag.txt"
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sample_sampler = "euler_a"
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optimizer_type = "Lion"
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learning_rate = 8e-5
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optimizer_args = [ "weight_decay=0.01", "betas=.95,.98",]
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lr_scheduler = "cosine_with_restarts"
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min_snr_gamma = 5.0
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unet_lr = 8e-5
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text_encoder_lr = 8e-6
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network_module = "networks.lora"
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network_dim = 128
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network_alpha = 64.0
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training_comment = "Flat_painted_lineart_illustration_sukaka"
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