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35 lines
1.9 KiB
Bash
35 lines
1.9 KiB
Bash
accelerate launch examples/wanvideo/model_training/train.py \
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--dataset_base_path data/example_video_dataset \
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--dataset_metadata_path data/example_video_dataset/metadata.csv \
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--height 480 \
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--width 832 \
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--dataset_repeat 1 \
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--model_id_with_origin_paths "Wan-AI/Wan2.1-I2V-14B-480P:diffusion_pytorch_model*.safetensors,Wan-AI/Wan2.1-I2V-14B-480P:models_t5_umt5-xxl-enc-bf16.pth,Wan-AI/Wan2.1-I2V-14B-480P:Wan2.1_VAE.pth,Wan-AI/Wan2.1-I2V-14B-480P:models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth" \
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--learning_rate 1e-4 \
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--num_epochs 5 \
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--remove_prefix_in_ckpt "pipe.dit." \
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--output_path "./models/train/Wan2.1-I2V-14B-480P_lora_split_cache" \
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--lora_base_model "dit" \
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--lora_target_modules "q,k,v,o,ffn.0,ffn.2" \
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--lora_rank 32 \
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--extra_inputs "input_image" \
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--task "sft:data_process" \
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--offload_models "Wan-AI/Wan2.1-I2V-14B-480P:diffusion_pytorch_model*.safetensors"
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accelerate launch examples/wanvideo/model_training/train.py \
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--dataset_base_path "./models/train/Wan2.1-I2V-14B-480P_lora_split_cache" \
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--height 480 \
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--width 832 \
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--dataset_repeat 100 \
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--model_id_with_origin_paths "Wan-AI/Wan2.1-I2V-14B-480P:diffusion_pytorch_model*.safetensors,Wan-AI/Wan2.1-I2V-14B-480P:models_t5_umt5-xxl-enc-bf16.pth,Wan-AI/Wan2.1-I2V-14B-480P:Wan2.1_VAE.pth,Wan-AI/Wan2.1-I2V-14B-480P:models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth" \
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--learning_rate 1e-4 \
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--num_epochs 5 \
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--remove_prefix_in_ckpt "pipe.dit." \
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--output_path "./models/train/Wan2.1-I2V-14B-480P_lora_split" \
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--lora_base_model "dit" \
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--lora_target_modules "q,k,v,o,ffn.0,ffn.2" \
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--lora_rank 32 \
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--extra_inputs "input_image" \
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--task "sft:train" \
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--offload_models "Wan-AI/Wan2.1-I2V-14B-480P:models_t5_umt5-xxl-enc-bf16.pth,Wan-AI/Wan2.1-I2V-14B-480P:Wan2.1_VAE.pth,Wan-AI/Wan2.1-I2V-14B-480P:models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth"
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