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33 lines
1.7 KiB
Markdown
33 lines
1.7 KiB
Markdown
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* dataset
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* `--dataset_base_path`: Base path of the Dataset.
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* `--dataset_metadata_path`: Metadata path of the Dataset.
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* `--height`: Image or video height. Leave `height` and `width` None to enable dynamic resolution.
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* `--width`: Image or video width. Leave `height` and `width` None to enable dynamic resolution.
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* `--num_frames`: Number of frames in each video. The frames are sampled from the prefix.
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* `--data_file_keys`: Data file keys in metadata. Separated by commas.
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* `--dataset_repeat`: Number of times the dataset is repeated in each epoch.
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* Model
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* `--model_paths`: Model paths to be loaded. JSON format.
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* `--model_id_with_origin_paths`: Model ID with original path, e.g., Wan-AI/Wan2.1-T2V-1.3B:diffusion_pytorch_model*.safetensors. Separated by commas.
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* Training
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* `--learning_rate`: Learning rate.
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* `--num_epochs`: Number of epochs.
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* `--output_path`: Save path.
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* `--remove_prefix_in_ckpt`: Remove prefix in ckpt.
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* Trainable module
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* `--trainable_models`: Trainable models, e.g., dit, vae, text_encoder.
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* `--lora_base_model`: Add LoRA on which model.
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* `--lora_target_modules`: Add LoRA on which layer.
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* `--lora_rank`: LoRA rank.
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* Extra model input
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* `--input_contains_input_image`: Model input contains `input_image`
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* `--input_contains_end_image`: Model input contains `end_image`.
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* `--input_contains_control_video`: Model input contains `control_video`.
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* `--input_contains_reference_image`: Model input contains `reference_image`.
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* `--input_contains_vace_video`: Model input contains `vace_video`.
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* `--input_contains_vace_reference_image`: Model input contains `vace_reference_image`.
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* `--input_contains_motion_bucket_id`: Model input contains `motion_bucket_id`.
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