jinyangchen Goto Github PK

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jinyangchen's Projects

albert_zh

A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型

bert

TensorFlow code and pre-trained models for BERT

bert-chinese-classification-task

bert中文分类实践

bert_paper_chinese_translation

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 论文的中文翻译 Chinese Translation!

cdcs

Chinese Data Competitions' Solutions

chinese-word-vectors

100+ Chinese Word Vectors 上百种预训练中文词向量

chineseembedding

Chinese Embedding collection incling token ,postag ,pinyin,dependency,word embedding.中文自然语言处理向量合集,包括字向量,拼音向量,词向量,词性向量,依存关系向量.共5种类型的向量

complexeventextraction

A concept and obvious expression pattern collection of Chinese compound event extraction which then be evolved into ComplexEventGraph，本项目提出了中文复合事件的概念与显式模式，包括条件事件、因果事件、顺承事件、反转事件等事件抽取，并形成事理图谱。

covid-19

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

d2l-en

Interactive deep learning book with code, math, and discussions. Available in multi-frameworks. Adopted at 140 universities.

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被全球140所大学采用教学。

dgl-ke

High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.

dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

ernie

An Implementation of ERNIE For Language Understanding (including Pre-training models and Fine-tuning tools)

ernie-1

Source code and dataset for ACL 2019 paper "ERNIE: Enhanced Language Representation with Informative Entities"

fasttext

Library for fast text representation and classification.

gensim

Topic Modelling for Humans

glove

GloVe model for distributed word representation

gluon-nlp

NLP made easy

gnnpapers

Must-read papers on graph neural networks (GNN)

gpt-3

GPT-3: Language Models are Few-Shot Learners

jieba

结巴中文分词

kashgari

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.