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BERT (language model) - Wikipedia Next sentence prediction (NSP): In this task, BERT is trained to predict whether one sentence logically follows another For example, given two sentences, "The cat sat on the mat" and "It was a sunny day", BERT has to decide if the second sentence is a valid continuation of the first one
BERT 系列模型 | 菜鸟教程 BERT (Bidirectional Encoder Representations from Transformers)是2018年由Google提出的革命性自然语言处理模型，它彻底改变了NLP领域的研究和应用范式。
万字长文，带你搞懂什么是BERT模型（非常详细）看这一篇就够了！-CSDN博客 BERT 是 Bidirectional Encoder Representations from Transformers 的缩写，是一种为自然语言处理 (NLP) 领域设计的 开源 机器学习框架。 该框架起源于 2018 年，由 Google AI Language 的研究人员精心打造。
【BERT】详解BERT - 彼得虫 - 博客园 BERT，全称Bidirectional Encoder Representation of Transformer，首次提出于《BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding》一文中。
BERT模型介绍-腾讯云开发者社区-腾讯云 BERT（Bidirectional Encoder Representations from Transformers）是Google在2018年提出的一种预训练语言模型，它在自然语言处理（NLP）领域引起了广泛的关注和应用。
【一文读懂】从零开始理解BERT模型核心原理 - 知乎 BERT (Bidirectional Encoder Representations from Transformers) 侧重于“理解”任务： 从BERT的英文全称可知BERT模型采用的是 Transformer 的 编码器（Encoder）部分， 并以 掩码语言模型（Masked Language Model, MLM） 作为核心预训练任务。
What Is the BERT Model and How Does It Work? - Coursera BERT is a deep learning language model designed to improve the efficiency of natural language processing (NLP) tasks It is famous for its ability to consider context by analyzing the relationships between words in a sentence bidirectionally
HELM-BERT: A Transformer for Medium-sized Peptide Property Prediction Therapeutic peptides have emerged as a pivotal modality in modern drug discovery, occupying a chemically and topologically rich space While accurate prediction of their physicochemical properties is essential for accelerating peptide development, existing molecular language models rely on representations that fail to capture this complexity Atom-level SMILES notation generates long token