基于transformer架构的预训练语言模型展现出了明显的优越性,刷新了众多nlp下游任务的效果。但是预训练语言模型是从海量无监督数据集中学习知识,且模型规模一般都比较大(base:110m, large: 330m),模型的训练成本相较于之前 的rnn时代明显增加,为了强化预训练模型的训练效率,一系列优化策略被提出,例如:(1)混合精度训练...
L和H确定模型的深度和宽度,而A是Transformer的内部hyper-parameter,影响每个编码器可以关注的上下文关系的数量。BERT的两个pre-trained模型:BERTBASE(L = 12; H = 768; A= 12)和BERTLARGE(L = 24; H = 1024; A = 16) 。 图2分析了BERTBASE模型的不同部分的内存和理论计算要求 (measured in millions of...
Best results are achieved on the filtered corpus with the best models being large transformer-based models pretrained on contemporary German language. For the polarity classification accuracies of up to 90% are achieved. The accuracies become lower for settings with a higher number of classes, ...
methBERT is a tool based on BERT36, a large language model (LLM) based on the self-attention mechanism that achieved a significant breakthrough in many natural language processing (NLP) tasks and served as the baseline architecture in many other fields. Most described methods based on nanopore...
A medical multimodal large language model for future pandemics Article Open access 02 December 2023 Artificial intelligence-based methods for fusion of electronic health records and imaging data Article Open access 26 October 2022 Data availability Restrictions apply to the availability of the develo...
Pretrained large-scale language models have increasingly demonstrated high accuracy on many natural language processing (NLP) tasks. However, the limited weight storage and computational speed on hardware platforms have impeded the popularity of pretrained models, especially in the era of edge computing....
这种灵活性和可扩展性使得 MoD Transformers 在计算效率和模型性能优化方面具有巨大的潜力。 Reference Blog: FLOPS vs FLOPs Paper: Training Compute-Optimal Large Language Models Github Repo: Mixture-AI/Mixture-of-Depths Github Repo: keli-wen/AGI-Study 编辑于 2024-05-30 00:45・IP 属地广东...
This paper explores the potential of transformer-based foundation models to detect Atrial Fibrillation (AFIB) in electrocardiogram (ECG) processing, an arrhythmia specified as an irregular heart rhythm without patterns. We construct a language with tokens from heartbeat locations to detect irregular ...
Transformer-based large language models like BERT and GPT obtain state-of-the-art performance on multiple NLP tasks. BERT’s attention heads are functionally specialized and learn to approximate classical syntactic operations in order to produce contextualized natural language55,56. The rapidly developing...
Kakwani D, Kunchukuttan A, Golla S, Gokul NC, Bhattacharyya A, Khapra M M, Kumar P (2020) Indicnlpsuite: monolingual corpora, evaluation benchmarks and pre-trained multilingual language models for Indian languages. In: Findings of the association for computational linguistics: EMNLP 2020 , pp...