ae = "/home/Ubuntu/Downloads/ae.safetensors"
bucket_no_upscale = true
bucket_reso_steps = 64
cache_latents = true
cache_latents_to_disk = true
cache_text_encoder_outputs = true
cache_text_encoder_outputs_to_disk = true
caption_extension = ".txt"
clip_l = "/home/Ubuntu/Downloads/clip_l.safetensors"
discrete_flow_shift = 3.1582
dynamo_backend = "no"
epoch = 25
full_bf16 = true
gradient_accumulation_steps = 1
gradient_checkpointing = true
guidance_scale = 1.0
highvram = true
huber_c = 0.1
huber_schedule = "snr"
loss_type = "l2"
lr_scheduler = "constant"
lr_scheduler_args = []
lr_scheduler_num_cycles = 1
lr_scheduler_power = 1
max_bucket_reso = 2048
max_data_loader_n_workers = 0
max_timestep = 1000
max_train_steps = 10000
mem_eff_save = true
min_bucket_reso = 256
mixed_precision = "bf16"
model_prediction_type = "raw"
network_alpha = 128
network_args = []
network_dim = 128
network_module = "networks.lora_flux"
noise_offset_type = "Original"
optimizer_args = [ "scale_parameter=False", "relative_step=False", "warmup_init=False", "weight_decay=0.01",]
optimizer_type = "Adafactor"
output_dir = "/home/Ubuntu/apps/StableSwarmUI/Models/Lora"
output_name = "Rank_1_FAST_4x_GPU"
pretrained_model_name_or_path = "/home/Ubuntu/Downloads/flux1-dev.safetensors"
prior_loss_weight = 1
resolution = "1024,1024"
sample_prompts = "/home/Ubuntu/apps/StableSwarmUI/Models/Lora/sample/prompt.txt"
sample_sampler = "euler_a"
save_every_n_epochs = 1
save_model_as = "safetensors"
save_precision = "float"
sdpa = true
seed = 1
t5xxl = "/home/Ubuntu/Downloads/t5xxl_fp16.safetensors"
t5xxl_max_token_length = 512
text_encoder_lr = 0.0001
timestep_sampling = "sigmoid"
train_batch_size = 2
train_data_dir = "/home/Ubuntu/Downloads/flux_train/img"
unet_lr = 0.0001
vae_batch_size = 4
wandb_run_name = "Rank_1_FAST_4x_GPU"