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Browse files- dataset.toml +14 -0
- sample_prompts.txt +4 -0
- train.sh +34 -0
dataset.toml
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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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[[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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[[datasets.subsets]]
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image_dir = '/app/fluxgym/datasets/flux1dev-pitting-lora-rk16-random'
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class_tokens = 'pitting defect on galvanized steel, irregular pitted surface, rough grainy texture, dark pits, subtle metallic sheen, close-up industrial inspection photo, shallow depth of field, low contrast, dim lighting, shadowed edges, horizontal striations'
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num_repeats = 1
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sample_prompts.txt
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pitting defect on galvanized steel, irregular pitted surface, rough grainy texture, dark pits, subtle metallic sheen, close-up industrial inspection photo, shallow depth of field, low contrast, dim lighting, shadowed edges, horizontal striations
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small pitting defect on galvanized steel, irregular pitted surface, rough grainy texture, dark pits, subtle metallic sheen, close-up industrial inspection photo, shallow depth of field, low contrast, dim lighting, shadowed edges, horizontal striations
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medium-size pitting defect on galvanized steel, irregular pitted surface, rough grainy texture, dark pits, subtle metallic sheen, close-up industrial inspection photo, shallow depth of field, low contrast, dim lighting, shadowed edges, horizontal striations
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large pitting defect on galvanized steel, irregular pitted surface, rough grainy texture, dark pits, subtle metallic sheen, close-up industrial inspection photo, shallow depth of field, low contrast, dim lighting, shadowed edges, horizontal striations
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train.sh
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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 "/app/fluxgym/models/unet/flux1-dev.sft" \
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--clip_l "/app/fluxgym/models/clip/clip_l.safetensors" \
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--t5xxl "/app/fluxgym/models/clip/t5xxl_fp16.safetensors" \
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--ae "/app/fluxgym/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 8 \
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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 16 \
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--optimizer_type adamw8bit \--sample_prompts="/app/fluxgym/outputs/flux1dev-pitting-lora-rk16-random/sample_prompts.txt" --sample_every_n_steps="1000" \
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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 20 \
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--save_every_n_epochs 10 \
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--dataset_config "/app/fluxgym/outputs/flux1dev-pitting-lora-rk16-random/dataset.toml" \
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--output_dir "/app/fluxgym/outputs/flux1dev-pitting-lora-rk16-random" \
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--output_name flux1dev-pitting-lora-rk16-random \
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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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