332 Open source projects that are alternatives of or similar to Bert For Sequence Labeling And Text Classification

NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego

Pytorch-NLU，一个中文文本分类、序列标注工具包，支持中文长文本、短文本的多类、多标签分类任务，支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech ta…

word2vec, sentence2vec, machine reading comprehension, dialog system, text classification, pretrained language model (i.e., XLNet, BERT, ELMo, GPT), sequence labeling, information retrieval, information extraction (i.e., entity, relation and event extraction), knowledge graph, text generation, network embedding

Macadam是一个以Tensorflow(Keras)和bert4keras为基础，专注于文本分类、序列标注和关系抽取的自然语言处理工具包。支持RANDOM、WORD2VEC、FASTTEXT、BERT、ALBERT、ROBERTA、NEZHA、XLNET、ELECTRA、GPT-2等EMBEDDING嵌入; 支持FineTune、FastText、TextCNN、CharCNN、BiRNN、RCNN、DCNN、CRNN、DeepMoji、SelfAttention、HAN、Capsule等文本分类算法; 支持CRF、Bi-LSTM-CRF、CNN-LSTM、DGCNN、Bi-LSTM-LAN、Lattice-LSTM-Batch、MRC等序列标注算法。

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.

a Deep Learning Framework for Text

分别使用rnn/cnn/rcnn来实现根据患者描述，进行疾病诊断

Fast + Non-Autoregressive Grammatical Error Correction using BERT. Code and Pre-trained models for paper "Parallel Iterative Edit Models for Local Sequence Transduction": www.aclweb.org/anthology/D19-1435.pdf (EMNLP-IJCNLP 2019)

Text Classification in Turkish Texts with Bert

Python for Text Classification with Machine Learning in Python 3.6.

Empower Sequence Labeling with Task-Aware Neural Language Model | a PyTorch Tutorial to Sequence Labeling

OpenTC is a text classification engine using several algorithms in machine learning

Target-dependent sentiment classification in news articles reporting on political events. Includes a high-quality data set of over 11k sentences and a state-of-the-art classification model.

The missing SVM-based text classification module implementing HanLP's interface

[CIKM 2018] Weakly-Supervised Neural Text Classification

A ready to go text classification trainer based on synaptic (https://github.com/cazala/synaptic)

LSTM+CRF NER

Official Java client for the MonkeyLearn API. Build and consume machine learning models for language processing from your Java apps.

Kaggle Twitter Sentiment Analysis Competition

HiGitClass: Keyword-Driven Hierarchical Classification of GitHub Repositories (ICDM'19)

ACL 2018: Hybrid semi-Markov CRF for Neural Sequence Labeling (http://aclweb.org/anthology/P18-2038)

Text preprocessing, representation, similarity calculation, text search and classification. Let's go and play with text!

Building a model to recognize incentives for landscape restoration in environmental policies from Latin America, the US and India. Bringing NLP to the world of policy analysis through an extensible framework that includes scraping, preprocessing, active learning and text analysis pipelines.

Text Similarity Applied to resume, to compare Resumes with Job Descriptions and create a score to rank them. Similar to an ATS.

Vietnamese Text Classification

Convolutional Neural Network for Text Classification in Keras

Open-source benchmark datasets and pretrained transformer models in the Filipino language.

[ACM-WSDM] 3rd place solution at WSDM Cup 2019, Fake News Classification on Kaggle.

【微信公众号：大邓和他的python】, Python语法快速入门https://www.bilibili.com/video/av44384851 Python网络爬虫快速入门https://www.bilibili.com/video/av72010301, 我的联系邮箱[email protected]

Using the Tsetlin Machine to learn human-interpretable rules for high-accuracy text categorization with medical applications

A Python implementation of a binary text classifier using Doc2Vec and SVM

A Japanese tokenizer based on recurrent neural networks

Multi-class text categorization using state-of-the-art pre-trained contextualized language models, e.g. BERT

Code for paper "Hierarchical Text Classification with Reinforced Label Assignment" EMNLP 2019

DeepClassifier is aimed at building general text classification model library.It's easy and user-friendly to build any text classification task.

BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)

Summary of my projects on kaggle

Nodejs binding for fasttext representation and classification.

Building a text classifier with extremely small datasets

2018-DC-“达观杯”文本智能处理挑战赛：冠军 (1st/3131)

The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"

Machine Learning (EE 5184) in NTU

A PyTorch-based toolkit for natural language processing

Official implementation of the paper “GECToR – Grammatical Error Correction: Tag, Not Rewrite” // Published on BEA15 Workshop (co-located with ACL 2020) https://www.aclweb.org/anthology/2020.bea-1.16.pdf

Caver: a toolkit for multilabel text classification.

BERT, LDA, and TFIDF based keyword extraction in Python

Library for fast text representation and extreme classification.

Detecting cyberbullying in tweets using Machine Learning

Repository containing code for the paper "Meta-Learning with Sparse Experience Replay for Lifelong Language Learning".

This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en

Multi-Class Text Classification for products based on their description with Machine Learning algorithms and Neural Networks (MLP, CNN, Distilbert).

Tensorflow implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)

Minimally Supervised Categorization of Text with Metadata (SIGIR'20)

This repo is a collection of AWESOME things about fake news detection, including papers, code, etc.

Active Learning for Text Classification in Python

Implementation of the paper "Hierarchical GRU for Utterance-level Emotion Recognition" in NAACL-2019.

Lbl2Vec learns jointly embedded label, document and word vectors to retrieve documents with predefined topics from an unlabeled document corpus.

a Fairseq fork for sequence tagging/labeling tasks

Implementing nlp papers relevant to classification with PyTorch, gluonnlp

Evidence-based Explanation Dataset (AACL-IJCNLP 2020)