FinerFact This is the PyTorch implementation for the FinerFact model in the AAAI 2022 paper Towards Fine-Grained Reasoning for Fake News Detection (Ar

Python Stop Words Table of contents Overview Available languages Installation Basic usage Python compatibility Overview Get list of common stop words

TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost

Kashgari Overview | Performance | Installation | Documentation | Contributing 🎉 🎉 🎉 We released the 2.0.0 version with TF2 Support. 🎉 🎉 🎉 If you

DELTA - A DEep learning Language Technology plAtform What is DELTA? DELTA is a deep learning based end-to-end natural language and speech processing p

Twitter COVID-19 Sentiment Analysis Members: Christopher Bach | Khalid Hamid Fallous | Jay Hirpara | Jing Tang | Graham Thomas | David Wetherhold Pro

多标签文本分类任务 近年来随着深度学习的发展，模型参数的数量飞速增长。为了训练这些参数，需要更大的数据集来避免过拟合。然而，对于大部分NLP任务来说，构建大规模的标注数据集非常困难（成本过高），特别是对于句法和语义相关的任务。相比之下，大规模的未标注语料库的构建则相对容易。为了利用这些数据，我们可以

spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from t

poutyne-transformers Train 🤗 -transformers models with Poutyne. Installation pip install poutyne-transformers Example import torch from transformers

Text Classification The purpose of this repository is to create a neural network model of NLP with deep learning for binary classification of texts re

PaddleNLP 2.0拥有丰富的模型库、简洁易用的API与高性能的分布式训练的能力，旨在为飞桨开发者提升文本建模效率，并提供基于PaddlePaddle 2.0的NLP领域最佳实践。

Summarization, translation, Q&A, text generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in alpha stag

n-stage Latent Dirichlet Allocation (n-LDA) Proposed n-LDA & A Novel Approach for classical LDA Latent Dirichlet Allocation (LDA) is a generative prob

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in

Accelerated deep learning R&D PyTorch framework for Deep Learning research and development. It focuses on reproducibility, rapid experimentation, and

CCF BDCI 2020 房产行业聊天问答匹配 A榜47/2985 赛题描述详见：https://www.datafountain.cn/competitions/474 文件说明 data: 存放训练数据和测试数据以及预处理代码 model_bert.py: 网络模型结构定义 adv_train

DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks Abstract: Adversarial training has been proven to

Text Classification Baseline Pipeline for fast building text classification TF-IDF + LogReg baselines. Usage Instead of writing custom code for specif

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, Text

Transfer Learning for Text Classification with Tensorflow Tensorflow implementation of Semi-supervised Sequence Learning(https://arxiv.org/abs/1511.01

EmTract: Extracting Emotions from Social Media Text Tailored for Financial Contexts EmTract is a tool that extracts emotions from social media text. I

Welcome to Healthsea ✨ Create better access to health with spaCy. Healthsea is a pipeline for analyzing user reviews to supplement products by extract

spaCy: Industrial-strength NLP spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest researc

spacy-streamlit: spaCy building blocks for Streamlit apps This package contains utilities for visualizing spaCy models and building interactive spaCy-

fastNLP fastNLP是一款轻量级的自然语言处理（NLP）工具包，目标是快速实现NLP任务以及构建复杂模型。 fastNLP具有如下的特性： 统一的Tabular式数据容器，简化数据预处理过程； 内置多种数据集的Loader和Pipe，省去预处理代码; 各种方便的NLP工具，例如Embedd

Machine Learning With Python Get started with Machine Learning with Python An engaging introduction to Machine Learning with Python TL;DR Download all

Text classification on IMDB dataset using Keras and Bi-LSTM Text classification on IMDB dataset using Keras and Bi-LSTM network. Usage python3 main.py

multi-label，classifier，text classification，多标签文本分类，文本分类，BERT，ALBERT，multi-label-classification，seq2seq，attention，beam search

Dual-Contrastive-Learning A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation". Y

LazyText is inspired b the idea of lazypredict, a library which helps build a lot of basic models without much code. LazyText is for text what lazypredict is for numeric data.

ZEROGEN This repository contains the code for our paper “ZeroGen: Efficient Zero

TextFooler A Model for Natural Language Attack on Text Classification and Inference This is the source code for the paper: Jin, Di, et al. "Is BERT Re

DeLFT DeLFT (Deep Learning Framework for Text) is a Keras and TensorFlow framework for text processing, focusing on sequence labelling (e.g. named ent

L3Cube-MahaCorpus L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources. We expand the existing Marathi monolingual

Text-AutoAugment (TAA) This repository contains the code for our paper Text AutoAugment: Learning Compositional Augmentation Policy for Text Classific

Code for EMNLP 2021 main conference paper "Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification"

tf-transformers: faster and easier state-of-the-art NLP in TensorFlow 2.0 ****************************************************************************

NLP Tutorial A list of NLP(Natural Language Processing) tutorials built on PyTorch. Table of Contents A step-by-step tutorial on how to implement and

Mail classification with tensorflow and MS Exchange Server (ham or spam).

You can watch the details of the project on my youtube channel Project Interface Project Second Interface Goal= Correctly guessing the classification

NLP Best Practices In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive bus

MonkeyLearn API for Python Official Python client for the MonkeyLearn API. Build and run machine learning models for language processing from your Pyt

Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more .

Patent Classification Goal: To train a machine learning classifier that can automatically classify international patents downloaded from the WIPO webs

FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,

FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,

Lbl2Vec Lbl2Vec is an algorithm for unsupervised document classification and unsupervised document retrieval. It automatically generates jointly embed

A Python package implementing a new model for text classification with visualization tools for Explainable AI 🍣 Online live demos: http://tworld.io/s

Snips NLU Snips NLU (Natural Language Understanding) is a Python library that allows to extract structured information from sentences written in natur

Trove Trove is a research framework for building weakly supervised (bio)medical named entity recognition (NER) and other entity attribute classifiers

WHAT: Supervised text vectorization tool Textvec is a text vectorization tool, with the aim to implement all the "classic" text vectorization NLP meth

Hierarchical Attention Networks for Document Classification This is an implementation of the paper Hierarchical Attention Networks for Document Classi

Active Learning allows you to efficiently label training data in a small-data scenario.

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 classifi

SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you

Hierarchical Metadata-Aware Document Categorization under Weak Supervision This project provides a weakly supervised framework for hierarchical metada

RATE: Overcoming Noise and Sparsity of Textual Features in Real-Time Location Estimation This is the implementation of RATE: Overcoming Noise and Spar