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  1. c3d1-000004.safetensors +3 -0
  2. dataset.toml +14 -0
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  39. sample_prompts.txt +3 -0
  40. train.sh +34 -0
c3d1-000004.safetensors ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:353830dfb5f895f70cc53a0056a26711dcf74ebb8fcebe937d3e6d995be3e4c4
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+ size 39763336
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 = 1024
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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 = '/app/fluxgym/datasets/c3d1'
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+ class_tokens = 'c3d1 man'
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+ num_repeats = 10
sample/c3d1_000100_00_20241016180843.png ADDED
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sample/c3d1_000100_02_20241016180854.png ADDED
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sample_prompts.txt ADDED
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+ c3d1 man eating ice cream, happy --42
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+ c3d1 man in a surreal virtual 3D world, --42
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+ c3d1 man riding a bear into battle, --42
train.sh 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 "/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 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 adamw8bit \--sample_prompts="/app/fluxgym/outputs/c3d1/sample_prompts.txt" --sample_every_n_steps="100" \
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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 4 \
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+ --dataset_config "/app/fluxgym/outputs/c3d1/dataset.toml" \
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+ --output_dir "/app/fluxgym/outputs/c3d1" \
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+ --output_name c3d1 \
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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 \