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English(EN) GoiBERT: Compact Vietnamese Language Models via Two-Stage Knowledge Distillation

GoiBERT:紧凑型越南语语言模型实现高性能

研究人员开发了GoiBERT,这是一个新系列的紧凑型越南语语言模型,旨在实现高效部署。这些模型拥有2600万和4900万参数,在包括文本分类和情感分析在内的各种基准测试中均表现出色。GoiBERT-large在同等规模的非教师模型中表现最佳,而GoiBERT-base的尺寸仅为强基线模型的四分之一,但性能却保持了近99%。这些模型通过两阶段知识蒸馏过程进行学习,利用互补的教师模型。 AI

影响 这些紧凑型模型可以显著降低越南语NLP应用的部署成本并提高其可访问性。

排序理由 该集群报道了一篇详细介绍新型语言模型创建和性能的学术论文。

在 arXiv cs.CL 阅读 →

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GoiBERT:紧凑型越南语语言模型实现高性能

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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Quang Anh Kiet Tran, Nam Anh Tran, Manh Hung Trinh, Thanh Danh Le, Khang Nhat Hoang Vo, Huynh Dai Nhan Tran ·

    GoiBERT:通过两阶段知识蒸馏实现紧凑型越南语语言模型

    arXiv:2610.30067v1 Announce Type: new Abstract: Vietnamese pre-trained encoders have improved rapidly, but the strongest ones are large, multilingual-vocabulary models or depend on external word segmentation, which makes them costly to deploy. We present GoiBERT, a family of two …

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    GoiBERT:通过两阶段知识蒸馏实现紧凑型越南语语言模型

    Vietnamese pre-trained encoders have improved rapidly, but the strongest ones are large, multilingual-vocabulary models or depend on external word segmentation, which makes them costly to deploy. We present GoiBERT, a family of two compact Vietnamese encoders with 26M and 49M par…