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29 lines
1.3 KiB
Bash
29 lines
1.3 KiB
Bash
export MODEL_DIR="stabilityai/stable-diffusion-xl-base-0.9"
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export OUTPUT_DIR="controlnet-0-9-canny"
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# --max_train_steps=15000 \
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accelerate launch train_controlnet_webdatasets.py \
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--pretrained_model_name_or_path=$MODEL_DIR \
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--pretrained_vae_model_name_or_path="madebyollin/sdxl-vae-fp16-fix" \
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--output_dir=$OUTPUT_DIR \
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--mixed_precision="fp16" \
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--resolution=1024 \
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--learning_rate=1e-5 \
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--max_train_steps=30000 \
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--max_train_samples=12000000 \
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--dataloader_num_workers=4 \
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--validation_image "./c_image_0.png" "./c_image_1.png" "./c_image_2.png" "./c_image_3.png" "./c_image_4.png" "./c_image_5.png" "./c_image_6.png" "./c_image_7.png" \
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--validation_prompt "beautiful room" "two paradise birds" "a snowy house behind a forest" "a couple watching a romantic sunset" "boats in the Amazonas" "a beautiful face of a woman" "a skater in Brooklyn" "a tornado in Iowa" \
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--train_shards_path_or_url "pipe:aws s3 cp s3://muse-datasets/laion-aesthetic6plus-data/{00000..01208}.tar -" \
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--eval_shards_path_or_url "pipe:aws s3 cp s3://muse-datasets/laion-aesthetic6plus-data/{01209..01210}.tar -" \
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--proportion_empty_prompts 0.5 \
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--validation_steps=1000 \
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--train_batch_size=12 \
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--gradient_checkpointing \
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--use_8bit_adam \
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--enable_xformers_memory_efficient_attention \
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--gradient_accumulation_steps=1 \
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--seed=42 \
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--report_to="wandb" \
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--push_to_hub
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