NCRF++: An Open-source Neural Sequence Labeling Toolkit

June 14, 2018 ยท Declared Dead ยท ๐Ÿ› Annual Meeting of the Association for Computational Linguistics

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Authors Jie Yang, Yue Zhang arXiv ID 1806.05626 Category cs.CL: Computation & Language Citations 190 Venue Annual Meeting of the Association for Computational Linguistics Last Checked 3 months ago
Abstract
This 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, 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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