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>THIS IS A MERGE of first 3 epochs loras</code></pre>looks like using all the 3 epochs at same time at weight 1 can improve style training with much less time 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_flux6" ^ --output_name "whimsical_flux6" ^ --save_model_as safetensors ^ --sdpa ^ --max_data_loader_n_workers 2 ^ --seed 777 ^ --gradient_checkpointing ^ --mixed_precision bf16 ^ --save_precision bf16 ^ --network_module networks.lora_flux ^ --network_dim 16 ^ --network_alpha 32 ^ --network_args train_blocks=single ^ --optimizer_type Prodigy ^ --lr_scheduler constant ^ --lr_scheduler_num_cycles 1 ^ --lr_scheduler_power 1 ^ --learning_rate 1 ^ --network_train_unet_only ^ --timestep_sampling sigmoid ^ --max_grad_norm 1 ^ --model_prediction_type raw ^ --apply_t5_attn_mask ^ --guidance_scale 1.0 ^ --min_bucket_reso 256 ^ --max_bucket_reso 2048 ^ --bucket_reso_steps 64 ^ --resolution 512,512 ^ --discrete_flow_shift 3 ^ --cache_text_encoder_outputs ^ --cache_text_encoder_outputs_to_disk ^ --cache_latents ^ --fp8_base ^ --enable_bucket ^ --split_mode ^ --caption_extension .txt ^ --keep_tokens 0 ^ --min_snr_gamma 7 ^ --save_every_n_epochs 1 ^ --train_batch_size "3" ^ --noise_offset 0.05 ^ --max_train_epochs 30 ^ --max_timestep 1000 ^ --adaptive_noise_scale 0<pre><code></code></pre>

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