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[model_arguments] |
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v2 = false |
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v_parameterization = false |
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pretrained_model_name_or_path = "/content/pretrained_model/model.ckpt" |
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|
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[additional_network_arguments] |
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no_metadata = false |
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unet_lr = 1.0 |
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text_encoder_lr = 1.0 |
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network_module = "networks.lora" |
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network_dim = 64 |
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network_alpha = 1 |
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network_train_unet_only = false |
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network_train_text_encoder_only = false |
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|
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[optimizer_arguments] |
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optimizer_type = "Prodigy" |
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learning_rate = 1.0 |
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max_grad_norm = 1.0 |
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optimizer_args = [ "decouple=True", "weight_decay=0.01", "d_coef=2", "use_bias_correction=True", "safeguard_warmup=True", "betas=0.9,0.99",] |
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lr_scheduler = "constant_with_warmup" |
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lr_warmup_steps = 100 |
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|
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[dataset_arguments] |
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cache_latents = true |
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debug_dataset = false |
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vae_batch_size = 4 |
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|
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[training_arguments] |
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output_dir = "/content/LoRA/output" |
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output_name = "nana" |
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save_precision = "fp16" |
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save_every_n_epochs = 10 |
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train_batch_size = 5 |
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max_token_length = 225 |
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mem_eff_attn = false |
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xformers = true |
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max_train_epochs = 20 |
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max_data_loader_n_workers = 8 |
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persistent_data_loader_workers = true |
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seed = 31337 |
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gradient_checkpointing = false |
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gradient_accumulation_steps = 1 |
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mixed_precision = "fp16" |
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clip_skip = 2 |
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logging_dir = "/content/LoRA/logs" |
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log_prefix = "nana" |
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lowram = true |
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multires_noise_discount = 0.3 |
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|
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[sample_prompt_arguments] |
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sample_every_n_epochs = 5 |
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sample_sampler = "ddim" |
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|
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[dreambooth_arguments] |
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prior_loss_weight = 1.0 |
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|
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[saving_arguments] |
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save_model_as = "safetensors" |
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|