these models shouldn't be used, it's about a private testing of different training parameters.I can't prevent you from downloading it =(Maybe in the future I will change this to a public space with more info to help people to train Flux D

it's_a_test

<pre><code>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</code></pre>

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