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Update README.md

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@@ -13,9 +13,9 @@ Video-BLADE is a data-free framework for efficient video generation. By jointly
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  ## πŸ“’ News
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- - **[Aug 2024]** πŸŽ‰ The code and pre-trained models for Video-BLADE have been released\!
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- - **[Aug 2024]** πŸ“ Support for two mainstream video generation models, CogVideoX-5B and WanX-1.3B, is now available.
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- - **[Aug 2024]** ⚑ Achieved high-quality video generation in just 8 steps, a significant speedup compared to the 50-step baseline.
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  ## ✨ Key Features
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@@ -185,7 +185,7 @@ bash train_tdm_1.sh
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  ```bash
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  # If not training with 8 GPUs, you must modify CUDA_VISIBLE_DEVICES and the num_processes in config.yaml
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- CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7,8 accelerate launch \
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  --config_file train/config.yaml \
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  train/train_cogvideo_tdm.py \
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  --pretrained_model_name_or_path CogVideoX-5b \ # Path to the base model
 
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  ## πŸ“’ News
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+ - **[Aug 2025]** πŸŽ‰ The code and pre-trained models for Video-BLADE have been released\!
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+ - **[Aug 2025]** πŸ“ Support for two mainstream video generation models, CogVideoX-5B and WanX-1.3B, is now available.
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+ - **[Aug 2025]** ⚑ Achieved high-quality video generation in just 8 steps, a significant speedup compared to the 50-step baseline.
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  ## ✨ Key Features
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  ```bash
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  # If not training with 8 GPUs, you must modify CUDA_VISIBLE_DEVICES and the num_processes in config.yaml
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+ CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 accelerate launch \
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  --config_file train/config.yaml \
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  train/train_cogvideo_tdm.py \
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  --pretrained_model_name_or_path CogVideoX-5b \ # Path to the base model