NLP Architect by Intel® AI Lab
Release: 0.1
Date: May 17, 2018
NLP Architect is an open-source Python library for exploring the state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding. It is intended to be a platform for future research and collaboration.
The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab.
NLP Architect can be downloaded from Github: https://github.com/NervanaSystems/nlp-architect
How can NLP Architect be used
- Train models using provided algorithms, reference datasets and configurations
- Train models using your own data
- Create new/extend models based on existing models or topologies
- Explore how deep learning models tackle various NLP tasks
- Experiment and optimize state-of-the-art deep learning algorithms
- integrate modules and utilities from the library to solutions
Library Overview
Research driven NLP/NLU models
The library contains state-of-art and novel NLP and NLU models in a varity of topics:- Dependency parsing
- Intent detection and Slot tagging model for Intent based applications
- Memory Networks for goal-oriented dialog
- Key-value Network for question&answer system
- Noun phrase embedding vectors model
- Noun phrase semantic segmentation
- NER and NE expansion
- Text chunking
- Reading comprehension
Deep Learning frameworks
Because of the current research nature of the library, several open source deep learning frameworks are used in this repository including:Overtime the list of models included in this space will change, though all generally run with Python 3.5+
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