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Fast Vocabulary Transfer for Language Model Compression

Leonidas Gee,Andrea Zugarini,Leonardo Rigutini,Paolo Torroni

2024 · DOI: 10.18653/v1/2022.emnlp-industry.41
Conference on Empirical Methods in Natural Language Processing · 50 Citations

TLDR

This work proposes a new method for model compression that relies on vocabulary transfer that can be effectively used in combination with other compression techniques, yielding a significant reduction in model size and inference time while marginally compromising on performance.

Abstract

Real-world business applications require a trade-off between language model performance and size. We propose a new method for model compression that relies on vocabulary transfer. We evaluate the method on various vertical domains and downstream tasks. Our results indicate that vocabulary transfer can be effectively used in combination with other compression techniques, yielding a significant reduction in model size and inference time while marginally compromising on performance.