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allennlp

An open-source NLP research library, built on PyTorch.

arctic-captions

astor

Python AST read/write

bilstm_crf

buaathesis

北航毕设论文LaTeX模板

codalab-worksheets

A collaborative platform for reproducible research (web interface and CLI).

datasets

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

dire

Neural Variable Renaming for Decompiled Binaries

dynet

DyNet: The Dynamic Neural Network Toolkit

dynet_nmt

A neural machine translation model in DyNet

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

filesys

improving-compgen-in-semparse

iscript

各种脚本 -- 关于 虾米 xiami.com, 百度网盘 pan.baidu.com, 115网盘 115.com, 网易音乐 music.163.com, 百度音乐 music.baidu.com, 360网盘/云盘 yunpan.cn, 视频解析 flvxz.com, bt torrent <--> magnet, ed2k, tumblr.com, unzip

keras

Theano-based Deep Learning library (convnets, recurrent neural networks, and more).

libsvm

libsvm.net

An easy and quick way to use the last libsvm library (3.16) in your .NET projects.

ltp

Language Technology Platform

markdown-content

Markdown content for the www.aerobatic.io website

md5test

my_fairseq

neural-symbolic-machines

Neural Symbolic Machines is a framework to integrate neural networks and symbolic representations using reinforcement learning, with applications in program synthesis and semantic parsing.

nl2code

A syntactic neural model for parsing natural language to executable code

nmt-tips

A tutorial about neural machine translation including tips on building practical systems

nn

A tiny neural network library

nn4nlp-code

Code Samples from Neural Networks for NLP

openie

Quality information extraction at web scale.

ospf_router

C++ implementation of the OSPF routing protocol

pbmt_assignment

11731 assignment 2

pynlpl

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).