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dataset.toml ADDED
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+ [general]
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+ shuffle_caption = false
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+ caption_extension = '.txt'
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+ keep_tokens = 1
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+
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+ [[datasets]]
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+ resolution = 512
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+ batch_size = 1
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+ keep_tokens = 1
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+
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+ [[datasets.subsets]]
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+ image_dir = 'C:\Users\micha\pinokio\api\fluxgym.git\datasets\youngkollegah'
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+ class_tokens = 'K0lleg4h08 person'
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+ num_repeats = 15
sample_prompts.txt ADDED
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+ K0lleg4h08 person is a body builder --d 42
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+ K0lleg4h08 person looking like a pimp in the redlight with a furcoat --d 42
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+ K0lleg4h08 person holding a bag full of weed infront a sign saying "Maastricht"
train.bat ADDED
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+ accelerate launch ^
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+ --mixed_precision bf16 ^
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+ --num_cpu_threads_per_process 1 ^
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+ sd-scripts/flux_train_network.py ^
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+ --pretrained_model_name_or_path "C:\Users\micha\pinokio\api\fluxgym.git\models\unet\flux1-dev.sft" ^
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+ --clip_l "C:\Users\micha\pinokio\api\fluxgym.git\models\clip\clip_l.safetensors" ^
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+ --t5xxl "C:\Users\micha\pinokio\api\fluxgym.git\models\clip\t5xxl_fp16.safetensors" ^
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+ --ae "C:\Users\micha\pinokio\api\fluxgym.git\models\vae\ae.sft" ^
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+ --cache_latents_to_disk ^
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+ --save_model_as safetensors ^
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+ --sdpa --persistent_data_loader_workers ^
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+ --max_data_loader_n_workers 2 ^
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+ --seed 42 ^
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+ --gradient_checkpointing ^
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+ --mixed_precision bf16 ^
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+ --save_precision bf16 ^
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+ --network_module networks.lora_flux ^
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+ --network_dim 4 ^
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+ --optimizer_type adafactor ^
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+ --optimizer_args "relative_step=False" "scale_parameter=False" "warmup_init=False" ^
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+ --lr_scheduler constant_with_warmup ^
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+ --max_grad_norm 0.0 ^
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+ --learning_rate 8e-4 ^
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+ --cache_text_encoder_outputs ^
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+ --cache_text_encoder_outputs_to_disk ^
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+ --fp8_base ^
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+ --highvram ^
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+ --max_train_epochs 16 ^
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+ --save_every_n_epochs 4 ^
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+ --dataset_config "C:\Users\micha\pinokio\api\fluxgym.git\outputs\youngkollegah\dataset.toml" ^
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+ --output_dir "C:\Users\micha\pinokio\api\fluxgym.git\outputs\youngkollegah" ^
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+ --output_name youngkollegah ^
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+ --timestep_sampling shift ^
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+ --discrete_flow_shift 3.1582 ^
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+ --model_prediction_type raw ^
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+ --guidance_scale 1 ^
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+ --loss_type l2 ^
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+ --save_state ^
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+ --save_state_on_train_end
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