Low-Rank Ternary Adaptation for Fine-Tuning Transformers
Ternary multiplicative adaptation is proposed, which represents discrete updates of ternary weights such as sign flips or zeroing through a low-rank Kronecker factorization into two small ternary matrices applied element-wise to ternary weights.
Alexandru-Dragos Manolache, Yun-qiang Li, Jan van Gemert
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