391 Open source projects that are alternatives of or similar to Lm Lstm Crf

reference pytorch code for named entity tagging

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

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF implement in pyotrch

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

Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling

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

a Fairseq fork for sequence tagging/labeling tasks

An Inplementation of CRF (Conditional Random Fields) in PyTorch 1.0

Learning Named Entity Tagger from Domain-Specific Dictionary

Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)

Named Entity Recognition (LSTM + CRF) - Tensorflow

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

PhoNLP: A BERT-based multi-task learning toolkit for part-of-speech tagging, named entity recognition and dependency parsing (NAACL 2021)

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。

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

datagrand 2019 information extraction competition rank9

Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0.

序列化标注工具，基于PyTorch实现BLSTM-CNN-CRF模型，CoNLL 2003 English NER测试集F1值为91.10%（word and char feature）。

keras attentional bi-LSTM-CRF for Joint NLU (slot-filling and intent detection) with ATIS

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。

中文自然语言的实体抽取和意图识别（Natural Language Understanding），可选Bi-LSTM + CRF 或者 IDCNN + CRF

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

中文NER的那些事儿

keras+bi-lstm+crf，中文命名实体识别

Chinese word segmentation in tensorflow 2.x

A Dataset of German Legal Documents for Named Entity Recognition

This repo contains a PyTorch implementation of a BiLSTM-CRF model for named entity recognition task.

KU_NERDY 이동엽, 임희석 (2017 국어 정보 처리 시스템경진대회 금상) - 한글 및 한국어 정보처리 학술대회

slot filling, intent detection, joint training, ATIS & SNIPS datasets, the Facebook’s multilingual dataset, MIT corpus, E-commerce Shopping Assistant (ECSA) dataset, CoNLL2003 NER, ELMo, BERT, XLNet

RNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.

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

LSTM-CRF in PyTorch

LSTM-CRF for NER with ConLL-2002 dataset

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%。

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

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

reference tensorflow code for named entity tagging

a Deep Learning Framework for Text

LSTM+CRF NER

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

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

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)

a sklearn wrapper for Google's BERT model

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.

面向中文电子病历的命名实体识别

No description or website provided.

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

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

BERT for Multitask Learning

Multi-label Classification with BERT; Fine Grained Sentiment Analysis from AI challenger

Open tools and data for cloudless automatic speech recognition

Seq2seq chatbot with attention and anti-language model to suppress generic response, option for further improve by deep reinforcement learning.

A python binding for crfsuite

The implementation of DeBERTa

Korean GPT-2 pretrained cased (KoGPT2)

A Lite Bert For Self-Supervised Learning Language Representations

👑 spaCy building blocks and visualizers for Streamlit apps

大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP

📖 Some language modeling tools for Keras