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cs.CL2024
ReTok: Replacing Tokenizer to Enhance Representation Efficiency in Large Language Model
Shuhao Gu, Mengdi Zhao, Bowen Zhang +3
Tokenizer is an essential component for large language models (LLMs), and a tokenizer with a high compression rate can improve the model's representation and processing efficiency.…
cs.CL2024
AquilaMoE: Efficient Training for MoE Models with Scale-Up and Scale-Out Strategies
Bo-Wen Zhang, Liangdong Wang, Ye Yuan +24
In recent years, with the rapid application of large language models across various fields, the scale of these models has gradually increased, and the resources required for their…