Most popular nlp repositories and open source projects

Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and natural-language tasks.

voice-builder

An opensource text-to-speech (TTS) voice building tool

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lingua-py

The most accurate natural language detection library for Python, suita...

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stanford-openie-python

Stanford Open Information Extraction made simple!

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OpenHowNet

Core Data of HowNet and OpenHowNet Python API

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text2sql-data

A collection of datasets that pair questions with SQL queries.

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ai-study

人工智能学习资料超全整理,包含机器学习基础ML、深度学习基础DL、计算机视...

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pinferencia

Python + Inference - Model Deployment library in Python. Simplest mode...

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vocabulary

[Not Maintained anymore] Python Module to get Meanings, Synonyms and w...

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KoELECTRA

Pretrained ELECTRA Model for Korean

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COMET

A Neural Framework for MT Evaluation

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NLP_Quickbook

NLP in Python with Deep Learning

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japanese-pretrained-models

Code for producing Japanese pretrained models provided by rinna Co., L...

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QA

使用深度学习算法实现的中文问答系统

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ML-paper-notes

:notebook: Notes and summaries of various ML, Computer Vision & NLP pa...

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awesome-nlp-sentiment-analysis

:book: 收集NLP领域相关的数据集、论文、开源实现,尤其是情感分析、情绪原...

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firefox-translations

Firefox Translations is a webextension that enables client side transl...

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m3tl

BERT for Multitask Learning

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tock

Tock, the open source conversational AI toolkit.

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weixin_public_corpus

微信公众号语料库

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Wordless

An Integrated Corpus Tool With Multilingual Support for the Study of L...

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nlprule

A fast, low-resource Natural Language Processing and Text Correction l...

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chatglm.cpp

C++ implementation of ChatGLM-6B & ChatGLM2-6B

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MacBERT

Revisiting Pre-trained Models for Chinese Natural Language Processing...

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text_mining_resources

Resources for learning about Text Mining and Natural Language Processi...

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text_summurization_abstractive_methods

Multiple implementations for abstractive text summurization , using go...

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happy-transformer

Happy Transformer makes it easy to fine-tune and perform inference wit...

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headlines

Automatically generate headlines to short articles

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Deep-Semantic-Similarity-Model

My Keras implementation of the Deep Semantic Similarity Model (DSSM)/C...

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awesome-tensorflow-2

👉 Tensorflow 2.x resources such as tutorial, blog, code and videos

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hands-on-nltk-tutorial

The hands-on NLTK tutorial for NLP in Python

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EventExtractionPapers

A list of NLP resources focused on event extraction task

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Mengzi

Mengzi Pretrained Models

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Goopt

🔍 Search Engine for a Procedural Simulation of the Web with GPT-3.

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bigbird

Transformers for Longer Sequences

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awesome-sentiment-analysis

Repository with all what is necessary for sentiment analysis and relat...

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OmniNet

Official Pytorch implementation of "OmniNet: A unified architecture fo...

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prompt-tuning

Original Implementation of Prompt Tuning from Lester, et al, 2021

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LightAutoML

Fast and customizable framework for automatic ML model creation (AutoM...

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Daily-DeepLearning

🔥机器学习/深度学习/Python/算法面试/自然语言处理教程/剑指offer/machine...

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python-stanford-corenlp

Python interface to CoreNLP using a bidirectional server-client interf...

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datasets-server

Lightweight web API for visualizing and exploring all types of dataset...

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machine-learning-articles

Monthly Series - Top 10 Machine Learning Articles

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awesome-data-annotation

A list of tools for annotating data, managing annotations, etc.

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keras-nlp

Modular Natural Language Processing workflows with Keras

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attn2d

Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequenc...

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VnCoreNLP

A Vietnamese natural language processing toolkit (NAACL 2018)

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Event-Extraction

基于法律裁判文书的事件抽取及其应用,包括数据的分词、词性标注、命名实体...

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CPM-Live

Live Training for Open-source Big Models

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prodigy-recipes

🍳 Recipes for the Prodigy, our fully scriptable annotation tool

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matchbox

Write PyTorch code at the level of individual examples, then run it ef...

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