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cmnfriend avatar cmnfriend commented on August 9, 2024

如果传入的模型没有Lora adapter，那么lora_A/B的维度会是0。每次训练时新初始化一个loranew_A/B，固定lora_A/B，训练完之后将loranew_A/B合并到lora_A/B中，然后保存lora_A/B。

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purpleofdial avatar purpleofdial commented on August 9, 2024

感谢您的及时回复！

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WuNein avatar WuNein commented on August 9, 2024

如果传入的模型没有Lora adapter，那么lora_A/B的维度会是0。每次训练时新初始化一个loranew_A/B，固定lora_A/B，训练完之后将loranew_A/B合并到lora_A/B中，然后保存lora_A/B。

所以新来的Task的LoRA是随机初始化的吧，我没理解错吧~
本来想基于先前任务初始化，从先前任务的矩阵出发，然后应用某种正交化过程来生成新任务的矩阵。例如，可以使用如 Gram-Schmidt 正交化过程来从现有矩阵派生出新的正交矩阵。想了一下感觉好麻烦）

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