Yoshinari Fujinuma (akkikiki)

akkikiki

Geek Repo

Company:AWS AI Labs

Location:New York, USA

Home Page:http://akkikiki.github.io

Twitter:@akkikiki

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Yoshinari Fujinuma's starred repositories

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Language:PythonLicense:Apache-2.0Stargazers:129749Issues:1120Issues:15306

fairseq

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

Language:PythonLicense:MITStargazers:29876Issues:424Issues:4173

language-server-protocol

Defines a common protocol for language servers.

Language:HTMLLicense:CC-BY-4.0Stargazers:10961Issues:261Issues:1104

tokenizers

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

Language:RustLicense:Apache-2.0Stargazers:8740Issues:122Issues:960

mesh-transformer-jax

Model parallel transformers in JAX and Haiku

Language:PythonLicense:Apache-2.0Stargazers:6250Issues:112Issues:205

pygcn

Graph Convolutional Networks in PyTorch

Language:PythonLicense:MITStargazers:5116Issues:55Issues:70

PLMpapers

Must-read Papers on pre-trained language models.

XLM

PyTorch original implementation of Cross-lingual Language Model Pretraining.

Language:PythonLicense:NOASSERTIONStargazers:2869Issues:57Issues:334

adapters

A Unified Library for Parameter-Efficient and Modular Transfer Learning

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:2479Issues:30Issues:376

MT-Reading-List

A machine translation reading list maintained by Tsinghua Natural Language Processing Group

Language:TeXLicense:BSD-3-ClauseStargazers:2418Issues:166Issues:23

awesome-sentence-embedding

A curated list of pretrained sentence and word embedding models

Language:PythonLicense:GPL-3.0Stargazers:2203Issues:77Issues:19

powerful-gnns

How Powerful are Graph Neural Networks?

Language:PythonLicense:MITStargazers:1163Issues:26Issues:23

GNNs-for-NLP

Tutorial: Graph Neural Networks for Natural Language Processing at EMNLP 2019 and CODS-COMAD 2020

pycountry

A Python library to access ISO country, subdivision, language, currency and script definitions and their translations.

Language:PythonLicense:LGPL-2.1Stargazers:725Issues:13Issues:135

naacl_transfer_learning_tutorial

Repository of code for the tutorial on Transfer Learning in NLP held at NAACL 2019 in Minneapolis, MN, USA

Language:PythonLicense:MITStargazers:720Issues:41Issues:4

xtreme

XTREME is a benchmark for the evaluation of the cross-lingual generalization ability of pre-trained multilingual models that covers 40 typologically diverse languages and includes nine tasks.

Language:PythonLicense:Apache-2.0Stargazers:624Issues:20Issues:68
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paws

This dataset contains 108,463 human-labeled and 656k noisily labeled pairs that feature the importance of modeling structure, context, and word order information for the problem of paraphrase identification.

Language:PythonLicense:NOASSERTIONStargazers:543Issues:14Issues:14

pixel

Research code for pixel-based encoders of language (PIXEL)

Language:PythonLicense:Apache-2.0Stargazers:327Issues:7Issues:16

ACL2022_KnowledgeNLP_Tutorial

Materials for ACL-2022 tutorial: Knowledge-Augmented Methods for Natural Language Processing

EMNLP-2019-Papers

Statistics and Accepted paper list with arXiv link of EMNLP-IJCNLP 2019

Language:Jupyter NotebookStargazers:234Issues:9Issues:0

multisense-prob-fasttext

ACL 2018 paper: Probabilistic FastText for Multi-Sense Word Embeddings (Athiwaratkun et al., 2018)

Language:C++License:NOASSERTIONStargazers:148Issues:10Issues:7

CrossLingualContextualEmb

Cross-Lingual Alignment of Contextual Word Embeddings

Language:PythonLicense:MITStargazers:97Issues:8Issues:10

WSDM2018_HyperQA

Reference Implementation for WSDM 2018 Paper "Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering"

teaspn-sdk

SDK for TEASPN, a framework and a protocol for integrated writing assistance environments

Language:PythonLicense:MITStargazers:60Issues:5Issues:5

allennlp-guide-examples

Example code, data, and commands for the AllenNLP guide

udapter

UDapter is a multilingual dependency parser that uses "contextual" adapters together with language-typology features for language-specific adaptation. This repository includes the code for "UDapter: Language Adaptation for Truly Universal Dependency Parsing"

Language:Jupyter NotebookLicense:MITStargazers:30Issues:4Issues:3

exploring-clmd-divergences

The code and data for the ACL paper

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