Delete config.json

config.json

@@ -1,47 +0,0 @@
-[network_arguments]
-unet_lr = 0.75
-text_encoder_lr = 0.75
-network_dim = 32
-network_alpha = 32
-network_module = "networks.lora"
-network_args = [ "conv_dim=32", "conv_alpha=16",]
-network_train_unet_only = false
-
-[optimizer_arguments]
-learning_rate = 0.75
-lr_scheduler = "cosine_with_restarts"
-lr_scheduler_num_cycles = 5
-lr_warmup_steps = 34
-optimizer_type = "Prodigy"
-optimizer_args = [ "weight_decay=0.1", "betas=[0.9,0.99]",]
-
-[training_arguments]
-pretrained_model_name_or_path = "sd_xl_base_1.0.safetensors"
-vae = "sdxl_vae.safetensors"
-max_train_epochs = 10
-train_batch_size = 4
-seed = 42
-max_token_length = 225
-xformers = false
-sdpa = true
-min_snr_gamma = 8.0
-lowram = false
-no_half_vae = true
-gradient_checkpointing = true
-gradient_accumulation_steps = 1
-max_data_loader_n_workers = 8
-persistent_data_loader_workers = true
-mixed_precision = "fp16"
-full_bf16 = false
-cache_latents = true
-cache_latents_to_disk = true
-cache_text_encoder_outputs = false
-min_timestep = 0
-max_timestep = 1000
-prior_loss_weight = 1.0
-
-[saving_arguments]
-save_precision = "fp16"
-save_model_as = "safetensors"
-save_every_n_epochs = 1
-save_last_n_epochs = 10