accelerate launch "./sd-scripts/flux_train_network.py" ^ --pretrained_model_name_or_path "D:\kohya_ss\flux\unet\flux1DevFp8_v10.safetensors" ^ --clip_l "D:/stable-diffusion-webui-forge-main/models/text_encoder/flux/clip_l.safetensors" ^ --t5xxl "D:/stable-diffusion-webui-forge-main/models/text_encoder/flux/flux1T5TextEncoder_stock.safetensors" ^ --ae "D:/stable-diffusion-webui-forge-main/models/VAE/flux/flux1DevVAE_stock.safetensors" ^ --train_data_dir "D:\kohya_ss\flux\img" ^ --output_dir "D:/kohya_ss/flux/models/whimsical_flux4" ^ --output_name "whimsical_flux4" ^ --save_model_as safetensors ^ --sdpa ^ --persistent_data_loader_workers ^ --max_data_loader_n_workers 2 ^ --seed 777 ^ --gradient_checkpointing ^ --mixed_precision bf16 ^ --save_precision fp16 ^ --network_module networks.lora_flux ^ --network_dim 24 ^ --network_alpha 24 ^ --network_args train_blocks=single rank_dropout=0.1 module_dropout=0.1 ^ --optimizer_type lion ^ --lr_scheduler cosine ^ --learning_rate 0.001 ^ --network_train_unet_only ^ --timestep_sampling sigmoid ^ --model_prediction_type raw ^ --guidance_scale 1.0 ^ --loss_type l2 ^ --resolution 512,512 ^ --cache_text_encoder_outputs ^ --cache_text_encoder_outputs_to_disk ^ --fp8_base ^ --enable_bucket ^ --bucket_no_upscale ^ --split_mode ^ --prior_loss_weight 1.0 ^ --caption_extension .txt ^ --keep_tokens 0 ^ --network_dropout 0.1 ^ --max_grad_norm 1.0 ^ --min_snr_gamma 10 ^ --save_every_n_epochs 1 ^ --train_batch_size "2" ^ --multires_noise_iterations 6 ^ --multires_noise_discount 0.3 ^ --optimizer_args weight_decay=0.4 betas="[0.95, 0.98]" ^ --max_train_epochs 30 ^ --enable_wildcard