HandsomeQD

ML-NLP

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

gensim

Topic Modelling for Humans

NLP_ability

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

KeyBERT

Minimal keyword extraction with BERT

NLP-Interview-Notes

该仓库主要记录 NLP 算法工程师相关的面试题

named_entity_recognition

中文命名实体识别（包括多种模型：HMM，CRF，BiLSTM，BiLSTM+CRF的具体实现）

yake

Single-document unsupervised keyword extraction

CLUENER2020

CLUENER2020 中文细粒度命名实体识别 Fine Grained Named Entity Recognition

lda

Topic modeling with latent Dirichlet allocation using Gibbs sampling

BERT-NER

Pytorch-Named-Entity-Recognition-with-BERT

contextualized-topic-models

A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).

tagger

Named Entity Recognition Tool

RAKE

A python implementation of the Rapid Automatic Keyword Extraction

Chinese-NLP-Corpus

Collections of Chinese NLP corpus

text-classification-surveys

文本分类资源汇总，包括深度学习文本分类模型，如SpanBERT、ALBERT、RoBerta、Xlnet、MT-DNN、BERT、TextGCN、MGAN、TextCapsule、SGNN、SGM、LEAM、ULMFiT、DGCNN、ELMo、RAM、DeepMoji、IAN、DPCNN、TopicRNN、LSTMN 、Multi-Task、HAN、CharCNN、Tree-LSTM、DAN、TextRCNN、Paragraph-Vec、TextCNN、DCNN、RNTN、MV-RNN、RAE等，浅层学习模型，如LightGBM 、SVM、XGboost、Random Forest、C4.5、CART、KNN、NB、HMM等。介绍文本分类数据集，如MR、SST、MPQA、IMDB、Yelp、20NG、AG、R8、DBpedia、Ohsumed、SQuAD、SNLI、MNLI、MSRP、MRDA、RCV1、AAPD，评价指标，如accuracy、Precision、Recall、F1、EM、MRR、HL、Micro-F1、Macro-F1、P@K，和技术挑战，包括多标签文本分类。

ETM

Topic Modeling in Embedding Spaces

python-topic-model

Implementation of various topic models

sccl

Pytorch implementation of Supporting Clustering with Contrastive Learning, NAACL 2021

Black-Box-Tuning

ICML'2022: Black-Box Tuning for Language-Model-as-a-Service & EMNLP'2022: BBTv2: Towards a Gradient-Free Future with Large Language Models

TRIME

[EMNLP 2022] Training Language Models with Memory Augmentation https://arxiv.org/abs/2205.12674

CoFiPruning

[ACL 2022] Structured Pruning Learns Compact and Accurate Models https://arxiv.org/abs/2204.00408

topicModelling

A project with topic model implementations

PyTorchOT

implements optimal transport algorithms in pytorch

jate

NEWS: JATE2.0 Beta.11 Released, see details below.

NER-FunTool

本NER项目包含多个中文数据集，模型采用BiLSTM+CRF、BERT+Softmax、BERT+Cascade、BERT+WOL等，最后用TFServing进行模型部署，线上推理和线下推理。

termsuite-core

A Java UIMA-based toolbox for multilingual and efficient terminology extraction an multilingual term alignment

atr4s

Toolkit with state-of-the-art Automatic Terms Recognition methods in Scala

JurisLMs

JurisLMs: Jurisprudential Language Models

NeuralSinkhornTopicModel

Neural Topic Model via Optimal Transport, ICLR 2021

TBXTools