2018
ACL
ACL 2018
NCRF++: An Open-source Neural Sequence Labeling Toolkit
Abstract
AbstractThis paper describes NCRF++, a toolkit for neural sequence labeling. NCRF++ is designed for quick implementation of different neural sequence labeling models with a CRF inference layer. It provides users with an inference for building the custom model structure through configuration file with flexible neural feature design and utilization. Built on PyTorch http://pytorch.org/, the core operations are calculated in batch, making the toolkit efficient with the acceleration of GPU. It also includes the implementations of most state-of-the-art neural sequence labeling models such as LSTM-CRF, facilitating reproducing and refinement on those methods.
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Trend Setter
— Large Language Models
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Keyword Pioneer
— gpu acceleration
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Speech & Audio
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Interdisciplinary Bridge
— Deep Learning and Natural Language Processing
Topics
Deep Learning > Architectures > Neural Networks
Natural Language Processing > Understanding > Named Entity Recognition
Natural Language Processing > Resources & Methods > Large Language Models
Natural Language Processing > Applications > Named Entity Recognition
Deep Learning > Models > Neural Networks
Deep Learning > Architectures > Recurrent Neural Networks