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41 lines
2.8 KiB
Bash
41 lines
2.8 KiB
Bash
modelscope download --dataset DiffSynth-Studio/diffsynth_example_dataset --include "qwen_image/Qwen-Image-Blockwise-ControlNet-Inpaint/*" --local_dir ./data/diffsynth_example_dataset
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accelerate launch --config_file examples/qwen_image/model_training/full/accelerate_config.yaml examples/qwen_image/model_training/train.py \
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--dataset_base_path data/diffsynth_example_dataset/qwen_image/Qwen-Image-Blockwise-ControlNet-Inpaint \
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--dataset_metadata_path data/diffsynth_example_dataset/qwen_image/Qwen-Image-Blockwise-ControlNet-Inpaint/metadata.csv \
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--data_file_keys "image,blockwise_controlnet_image,blockwise_controlnet_inpaint_mask" \
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--max_pixels 1048576 \
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--dataset_repeat 400 \
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--model_id_with_origin_paths "Qwen/Qwen-Image:transformer/diffusion_pytorch_model*.safetensors,Qwen/Qwen-Image:text_encoder/model*.safetensors,Qwen/Qwen-Image:vae/diffusion_pytorch_model.safetensors,DiffSynth-Studio/Qwen-Image-Blockwise-ControlNet-Inpaint:model.safetensors" \
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--learning_rate 1e-3 \
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--num_epochs 2 \
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--remove_prefix_in_ckpt "pipe.blockwise_controlnet.models.0." \
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--output_path "./models/train/Qwen-Image-Blockwise-ControlNet-Inpaint_full" \
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--trainable_models "blockwise_controlnet" \
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--extra_inputs "blockwise_controlnet_image,blockwise_controlnet_inpaint_mask" \
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--use_gradient_checkpointing \
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--find_unused_parameters
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# If you want to pre-train a Inpaint Blockwise ControlNet from scratch,
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# please run the following script to first generate the initialized model weights file,
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# and then start training with a high learning rate (1e-3).
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# python examples/qwen_image/model_training/scripts/Qwen-Image-Blockwise-ControlNet-Inpaint-Initialize.py
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# accelerate launch --config_file examples/qwen_image/model_training/full/accelerate_config.yaml examples/qwen_image/model_training/train.py \
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# --dataset_base_path data/diffsynth_example_dataset/qwen_image/Qwen-Image-Blockwise-ControlNet-Inpaint \
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# --dataset_metadata_path data/diffsynth_example_dataset/qwen_image/Qwen-Image-Blockwise-ControlNet-Inpaint/metadata.csv \
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# --data_file_keys "image,blockwise_controlnet_image,blockwise_controlnet_inpaint_mask" \
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# --max_pixels 1048576 \
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# --dataset_repeat 50 \
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# --model_id_with_origin_paths "Qwen/Qwen-Image:transformer/diffusion_pytorch_model*.safetensors,Qwen/Qwen-Image:text_encoder/model*.safetensors,Qwen/Qwen-Image:vae/diffusion_pytorch_model.safetensors" \
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# --model_paths '["models/blockwise_controlnet_inpaint.safetensors"]' \
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# --learning_rate 1e-3 \
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# --num_epochs 2 \
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# --remove_prefix_in_ckpt "pipe.blockwise_controlnet.models.0." \
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# --output_path "./models/train/Qwen-Image-Blockwise-ControlNet-Inpaint_full" \
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# --trainable_models "blockwise_controlnet" \
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# --extra_inputs "blockwise_controlnet_image,blockwise_controlnet_inpaint_mask" \
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# --use_gradient_checkpointing \
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# --find_unused_parameters
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