Neural Monkey: Neural Sequence Learning Using TensorFlow. The Neural Monkey package provides a higher level abstraction for sequential neural network models, most prominently in Natural Language Processing (NLP). It is built on TensorFlow. It can be used for fast prototyping of sequential models in NLP which can be used e.g. for neural machine translation or sentence classification. The higher-level API brings together a collection of standard building blocks (RNN encoder and decoder, multi-layer perceptron) and a simple way of adding new building blocks implemented directly in TensorFlow.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Albert Zeyer, Tamer Alkhouli, Hermann Ney: RETURNN as a Generic Flexible Neural Toolkit with Application to Translation and Speech Recognition (2018) arXiv
- Felix Hieber, Tobias Domhan, Michael Denkowski, David Vilar, Artem Sokolov, Ann Clifton, Matt Post: Sockeye: A Toolkit for Neural Machine Translation (2017) arXiv