Jhih-Jie Chen's starred repositories
reformer_lm
a Pytorch implementation of the Reformer Network (https://openreview.net/pdf?id=rkgNKkHtvB)
spacy-stanza
💥 Use the latest Stanza (StanfordNLP) research models directly in spaCy
bert-sense
Source code accompanying the KONVENS 2019 paper "Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings"
python-ftfy
Fixes mojibake and other glitches in Unicode text, after the fact.
word_sense_disambigation_corpora
SemCor and Masc documents annotated with NOAD word senses.
Annotated-WikiExtractor
Simple Wikipedia plain text extractor with article link annotations and Hadoop support.
sacremoses
Python port of Moses tokenizer, truecaser and normalizer
NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
cc-pyspark
Process Common Crawl data with Python and Spark
wiki-error-corpus
Scripts for extracting errors from Wikipedia revisions
languagetool
Style and Grammar Checker for 25+ Languages
sequence-labeler
Neural network sequence labeling model
lang-8-process
Lang-8 preprocessing scripts
gec-pseudodata
Repository of "An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction" (EMNLP-IJCNLP 2019)
python-crfsuite
A python binding for crfsuite
neural-naacl2018
Neural models and instructions on how to reproduce our results for our neural grammatical error correction systems from M. Junczys-Dowmunt, R. Grundkiewicz, S. Guha, K. Heafield: Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task, NAACL 2018.
cython_hunspell
Cython wrapper on Hunspell Dictionary
spacy-transformers
🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
terminals-are-sexy
💥 A curated list of Terminal frameworks, plugins & resources for CLI lovers.
How-To-Secure-A-Linux-Server
An evolving how-to guide for securing a Linux server.
dep-cross-domain
[ACL'19] Code for "Semi-supervised Domain Adaptation for Dependency Parsing"