122 Open source projects that are alternatives of or similar to Sltk

Implemention of FCN-8 and FCN-16 with Keras and uses CRF as post processing

Keras solution of Chinese NER task using BiLSTM-CRF/BiGRU-CRF/IDCNN-CRF model with Pretrained Language Model: supporting BERT/RoBERTa/ALBERT

g2pC: A Context-aware Grapheme-to-Phoneme Conversion module for Chinese

Benchmark Arabic text diacritization dataset

Inference with state-of-the-art models (pre-trained by LD-Net / AutoNER / VanillaNER / ...)

Source codes and corpora of paper "Iterated Dilated Convolutions for Chinese Word Segmentation"

crf-seg:用于生产环境的中文分词处理工具，可自定义语料、可自定义模型、架构清晰，分词效果好。java编写。

遥感图像的语义分割，基于深度学习，在Tensorflow框架下，利用TF.Keras，运行环境TF2.0+

a Fairseq fork for sequence tagging/labeling tasks

命名体识别(NER)综述-论文-模型-代码(BiLSTM-CRF/BERT-CRF)-竞赛资源总结-随时更新

Conditional Random Fields as Recurrent Neural Networks (Tensorflow)

Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.

Test specified presets/CRF values for the x264 or x265 encoder. Compares VMAF/SSIM/PSNR numerically & via graphs.

Causality Extraction based on Self-Attentive BiLSTM-CRF with Transferred Embeddings

Chinese & English Cws Pos Ner Entity Recognition implement using CNN bi-directional lstm and crf model with char embedding.基于字向量的CNN池化双向BiLSTM与CRF模型的网络，可能一体化的完成中文和英文分词，词性标注，实体识别。主要包括原始文本数据，数据转换,训练脚本,预训练模型,可用于序列标注研究.注意：唯一需要实现的逻辑是将用户数据转化为序列模型。分词准确率约为93%，词性标注准确率约为90%，实体标注（在本样本上）约为85%。

BERT-BiLSTM-CRF的Keras版实现

Tutorial for End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF

Entity recognition codes for "2019 Datagrand Cup: Text Information Extraction Challenge"

A machine learning software for extracting information from scholarly documents

🎨 🎨NLP 自然语言处理教程 🎨🎨 https://dataxujing.github.io/NLP-paper/

The classical BiLSTM-CRF model implemented in Tensorflow, for sequence labeling tasks. In Vex version, everything is configurable.

Edge-aware U-Net with CRF-RNN layer for Medical Image Segmentation

CrossNER: Evaluating Cross-Domain Named Entity Recognition (AAAI-2021)

Tensorflow-LSTM-CRF tool for Named Entity Recognizer

GROBID extension for identifying and normalizing physical quantities.

Basic exercises of chinese information processing

🌈 Implementation of Neural Network based Named Entity Recognizer (Lample+, 2016) using Chainer.

A TensorFlow implementation of Recurrent Neural Networks for Sequence Classification and Sequence Labeling

Implementation of NeurIPS 20 paper: Latent Template Induction with Gumbel-CRFs

自然语言处理工具Macropodus，基于Albert+BiLSTM+CRF深度学习网络架构，中文分词，词性标注，命名实体识别，新词发现，关键词，文本摘要，文本相似度，科学计算器，中文数字阿拉伯数字(罗马数字)转换，中文繁简转换，拼音转换。tookit(tool) of NLP，CWS(chinese word segnment)，POS(Part-Of-Speech Tagging)，NER(name entity recognition)，Find(new words discovery)，Keyword(keyword extraction)，Summarize(text summarization)，Sim(text similarity)，Calculate(scientific calculator)，Chi2num(chinese number to arabic number)

sequence tagging for NER for ULMFiT

A python binding for crfsuite

基于vue3 element plus的快速表单生成器

Deep neural models for core NLP tasks (Pytorch version)

开源中文分词工具包，中文分词Web API，Lucene中文分词，中英文混合分词

Hierarchically-Refined Label Attention Network for Sequence Labeling

AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging (ACL 2019 Demo)

KoBERT와 CRF로 만든 한국어 개체명인식기 (BERT+CRF based Named Entity Recognition model for Korean)

A TensorFlow implementation of Neural Sequence Labeling model, which is able to tackle sequence labeling tasks such as POS Tagging, Chunking, NER, Punctuation Restoration and etc.

把李航老师《统计学习方法》的后几章的算法都用java实现了一遍，实现盒子与球的EM算法，扩展到去GMM训练，后来实现了HMM分词（实现了HMM分词的参数训练）和CRF分词（借用CRF++训练的参数模型），最后利用tensorFlow把BiLSTM+CRF实现了，然后为lucene包装了一个XinAnalyzer

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。

C++ based implementation of StatNLP framework

Helsinki Prosody Corpus and A System for Predicting Prosodic Prominence from Text

A HMM-like linear-chain CRF, used Tensorflow API. 🐣

a Deep Learning Framework for Text

Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.

《统计学习方法》与常见机器学习模型(GBDT/XGBoost/lightGBM/FM/FFM)的原理讲解与python和类库实现

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

A Dataset of German Legal Documents for Named Entity Recognition

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

WRENCH: Weak supeRvision bENCHmark

A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)

A neural network layer that enables training of deep neural networks directly from crowdsourced labels (e.g. from Amazon Mechanical Turk) or, more generally, labels from multiple annotators with different biases and levels of expertise.

Easy to use NLP library built on PyTorch and TorchText

An easy-to-use named entity recognition (NER) toolkit, implemented the Bi-LSTM+CRF model in tensorflow.

pytorch实现bert做seq2seq任务，使用unilm方案,现在也可以做自动摘要，文本分类，情感分析，NER，词性标注等任务,支持GPT2进行文章续写。

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

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)

自然语言处理常见任务（主要包括文本分类，序列标注，自动问答等）解决方案试验田

NLP for human. A fast and easy-to-use natural language processing (NLP) toolkit, satisfying your imagination about NLP.