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bucket_reso_steps = 32
cache_latents = true
cache_latents_to_disk = true
caption_extension = ".txt"
clip_skip = 2
dynamo_backend = "no"
enable_bucket = true
epoch = 10
gradient_accumulation_steps = 1
gradient_checkpointing = true
huber_c = 0.1
huber_schedule = "snr"
learning_rate = 0.0002
log_with = "wandb"
logging_dir = "/root/autodl-tmp/logs/example"
loss_type = "l2"
lr_scheduler = "constant"
lr_scheduler_args = []
lr_scheduler_num_cycles = 1
lr_scheduler_power = 1
max_bucket_reso = 2176
max_data_loader_n_workers = 0
max_grad_norm = 1
max_timestep = 1000
max_token_length = 75
max_train_epochs = 10
max_train_steps = 22511
min_bucket_reso = 384
mixed_precision = "fp16"
network_alpha = 16
network_args = []
network_dim = 32
network_module = "networks.lora"
network_weights = "/root/kohya_ss/sd-models/arknight_all_v2.safetensors"
no_half_vae = true
noise_offset = 0.035
noise_offset_type = "Original"
optimizer_args = []
optimizer_type = "AdamW"
output_dir = "/root/kohya_ss/output5"
output_name = "arknight_all_v2_pro"
pretrained_model_name_or_path = "/root/kohya_ss/sd-models/pony-v6.safetensors"
prior_loss_weight = 1
resolution = "1024,1024"
sample_every_n_steps = 1000
sample_prompts = "/root/kohya_ss/output5/prompt.txt"
sample_sampler = "euler_a"
save_every_n_epochs = 1
save_last_n_steps_state = 1
save_model_as = "safetensors"
save_precision = "fp16"
seed = 12345
text_encoder_lr = 0.0001
train_batch_size = 50
train_data_dir = "/arkinghts_v2"
training_comment = "example"
unet_lr = 0.0001
wandb_api_key = "6cdd066d56acd416b1c1680133e37589511d81f7"
wandb_run_name = "GPU-使用率-温度检测"
xformers = true
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