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Update README.md

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@@ -27,6 +27,7 @@ cutoff_len: 8192
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  per_device_train_batch_size: 1
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  gradient_accumulation_steps: 16
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  learning_rate: 1.0e-5
 
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  num_train_epochs: 1.0
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  lr_scheduler_type: cosine
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  warmup_ratio: 0.05
@@ -107,7 +108,7 @@ print(output_text)
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  We are working on the release of a smaller, more efficient 3B model, which is designed to provide a balance between performance and resource efficiency. This model aims to deliver strong multimodal reasoning capabilities while being more accessible and optimized for environments with limited computational resources, offering a more compact alternative to the current 7B model.
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  ## R1-Onevision Authors
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- - Yi Yang*, Xiaoxuan He*, Hongkun Pan*, Xiyan Jiang, Yan Deng, Xingtao Yang, Haoyu Lu, Minfeng Zhu†, Bo Zhang†, Wei Chen
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  - *Equal contribution. †Corresponding authors.
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  ## Model Contact
 
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  per_device_train_batch_size: 1
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  gradient_accumulation_steps: 16
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  learning_rate: 1.0e-5
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+
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  num_train_epochs: 1.0
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  lr_scheduler_type: cosine
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  warmup_ratio: 0.05
 
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  We are working on the release of a smaller, more efficient 3B model, which is designed to provide a balance between performance and resource efficiency. This model aims to deliver strong multimodal reasoning capabilities while being more accessible and optimized for environments with limited computational resources, offering a more compact alternative to the current 7B model.
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  ## R1-Onevision Authors
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+ - Yi Yang*, Xiaoxuan He*, Hongkun Pan*, Xiyan Jiang, Yan Deng, Xingtao Yang, Haoyu Lu, Minfeng Zhu†, Bo Zhang†
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  - *Equal contribution. †Corresponding authors.
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  ## Model Contact