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config_lora-20250503-051050.toml

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+ae = "/workspace/ae.safetensors"
+apply_t5_attn_mask = true
+bucket_no_upscale = true
+bucket_reso_steps = 64
+cache_latents = true
+cache_latents_to_disk = true
+cache_text_encoder_outputs = true
+caption_extension = ".txt"
+clip_l = "/workspace/clip_l.safetensors"
+clip_skip = 1
+discrete_flow_shift = 3.0
+dynamo_backend = "no"
+enable_bucket = true
+epoch = 10
+gradient_accumulation_steps = 1
+gradient_checkpointing = true
+guidance_scale = 3.5
+huber_c = 0.1
+huber_scale = 1
+huber_schedule = "snr"
+logging_dir = "/workspace/formatted_training/log"
+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_grad_norm = 1
+max_timestep = 1000
+max_train_steps = 100
+mem_eff_attn = true
+mem_eff_save = true
+min_bucket_reso = 256
+mixed_precision = "fp16"
+model_prediction_type = "raw"
+network_alpha = 128
+network_args = [ "train_double_block_indices=all", "train_single_block_indices=all",]
+network_dim = 128
+network_module = "networks.lora_flux"
+network_train_unet_only = true
+noise_offset_type = "Original"
+optimizer_args = []
+optimizer_type = "Adafactor"
+output_dir = "/workspace/formatted_training/model"
+output_name = "mi_modelo_lora_v1"
+pretrained_model_name_or_path = "/workspace/flux1-dev.safetensors"
+prior_loss_weight = 1
+resolution = "512,640"
+sample_prompts = "/workspace/formatted_training/model/sample/prompt.txt"
+sample_sampler = "euler_a"
+save_every_n_epochs = 5
+save_model_as = "safetensors"
+save_precision = "fp16"
+t5xxl = "/workspace/t5xxl_fp16.safetensors"
+t5xxl_max_token_length = 512
+text_encoder_lr = []
+timestep_sampling = "sigmoid"
+train_batch_size = 2
+train_data_dir = "/workspace/formatted_training/img"
+unet_lr = 1e-5
+wandb_run_name = "mi_modelo_lora_v1"
+xformers = true