ganeshjawahar

mem_absa

Aspect Based Sentiment Analysis using End-to-End Memory Networks

interpret_bert

Interpreting Bidirectional Encoder Representations from Transformers (BERT)

torch-teacher

Compilation of the state-of-the-art neural models used in Machine Reading and Comprehension Task (in progress)

tweet-classify

Tweet Classification using RNN and CNN

tweet2vec

Implementation of the model presented in our ECIR 2017 paper

drl4nlp.scratchpad

Notes on Deep Reinforcement Learning for Natural Language Processing papers

dl4nlp-made-easy

Toy codes to kick-start deep learning for NLP !

ELMoLex

Final parser submitted by ParisNLP team for CoNLL 2018 Shared Task on Multilingual Parsing

social_word_emb

Contextualized Diachronic Word Representations

fast_text

Implementation of Facebook's FastText model in Torch

fine-tweet

https://arxiv.org/abs/1704.00898

interpretNode

Towards Interpretation of Node Embeddings

nlp-papernotes

Notes on recent Natural Language Processing papers

allennlp

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

Awesome-AutoDL

A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.

awesome-GNN-papers

cpsc330

CPSC 330: Applied Machine Learning

fairseq-1

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

ganeshjawahar.github.io

GLUECoS

A benchmark for code-switched NLP, ACL 2020

hardware-aware-transformers-1

[ACL'20] HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

ire-wiki-search

Java implementation of Search Engine for Wikipedia

nlp-datasets

A list of datasets/corpora for NLP tasks, in reverse chronological order.

once-for-all-bert

pyslides

(dropped)

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Stochastic-Mixture-of-Experts

This package implements THOR: Transformer with Stochastic Experts.

tf_nmt

understanding https://github.com/tensorflow/nmt

transformers

xtreme-distil-transformers

XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale