244 Open source projects that are alternatives of or similar to Hscrf Pytorch

Empower Sequence Labeling with Task-Aware Language Model

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

reference pytorch code for named entity tagging

LSTM+CRF NER

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

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

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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）。

Learning Named Entity Tagger from Domain-Specific Dictionary

LSTM-CRF for NER with ConLL-2002 dataset

a Fairseq fork for sequence tagging/labeling tasks

Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling

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

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

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)

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

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

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

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%。

datagrand 2019 information extraction competition rank9

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

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

Named Entity Recognition (LSTM + CRF) - Tensorflow

面向中文电子病历的命名实体识别

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

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。

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.

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

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

中文NER的那些事儿

reference tensorflow code for named entity tagging

keras+bi-lstm+crf，中文命名实体识别

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。

a Deep Learning Framework for Text

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

LSTM-CRF in PyTorch

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

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

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

Chinese word segmentation in tensorflow 2.x

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.

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.

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

A Dataset of German Legal Documents for Named Entity Recognition

Named-entity recognition for Ruby

PyTorch implementation of the paper: Vector Projection Network for Few-shot Slot Tagging in Natural Language Understanding. Su Zhu, Ruisheng Cao, Lu Chen and Kai Yu.

This package features data-science related tasks for developing new recognizers for Presidio. It is used for the evaluation of the entire system, as well as for evaluating specific PII recognizers or PII detection models.

CRF, Partial CRF and Marginal CRF in PyTorch

Basic exercises of chinese information processing

Language agnostic named entity recognizer

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

Python module for Named Entity Recognition (NER) using natural language processing.

chatbot_ner: Named Entity Recognition for chatbots.

BiLSTM_CRF中文实体命名识别

A Named-Entity Recogniser based on Grobid.

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

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

GROBID extension for identifying and normalizing physical quantities.