462 Open source projects that are alternatives of or similar to Zh Ner Keras

📰 A published weekly with a Thursday publication date.

Turn Chinese natural language into structured data 中文自然语言理解

Go 语言汉字转拼音工具

CNN-RNN中文文本分类，基于TensorFlow

Vim 实操教程（Learning Vim）Vim practical tutorial.

Chinese voice corpus. 中文语音语料，语音更加清晰自然，包含8个开源数据集，3200个说话人，900小时语音，1300万字。

PhoBERT: Pre-trained language models for Vietnamese (EMNLP-2020 Findings)

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)

中英文文案排版纠正器

swift-algorithm-club的翻译。使用Swift学习算法和数据结构。

Medical Concept Annotation Tool

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。

🏡 Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.

Convert Chinese Characters to Single-Line Fonts using Computer Vision

🦖 长期维护！中文圈下与 Deno 相关的 Awesome 资源全图谱

🇨🇳Open Chinese Convert is an opensource project for conversion between Traditional Chinese and Simplified Chinese.(java 中文繁简体转换)

Borgert is a CMS Open Source created with Laravel Framework 5.6

自动修正中文、英文、代码混合排版中的全半角、空格等问题

Large-scale Pre-training Corpus for Chinese 100G 中文预训练语料

RoBERTa中文预训练模型: RoBERTa for Chinese

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

awesome项目中文翻译，提升查阅效率

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

Procedurally generated paintings of nonexistent flowers.

基于BERT的中文命名实体识别

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

资治通鉴易读版

前任作者NekoInverter在gitlab重新更新EhViewer了，我不再独立维护项目，本项目暂时封存。 请前往 https://gitlab.com/NekoInverter/EhViewer 获取最新版本。

using bilstm-crf,bert and other methods to do sequence tagging task

language model in Chinese，基于Pytorch官方文档实现

PHP Best Practices（中译版）

پیکره بزرگ شناسایی موجودیت‌های نامدار فارسی برچسب خورده

<<Rust语言圣经(Book & Course)>>对Rust语言进行全面且深入的讲解，书中辅以生动的示例和习题，带你攻克从入门学习到实践应用的各种难关。 我们的目标是做一门优秀的开源Rust教程(课程)——学Rust就上course.rs。

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

可能是最完整的 sqlmap 中文文档。

BNLP is a natural language processing toolkit for Bengali Language.

FewCLUE 小样本学习测评基准，中文版

LSTM-CRF for NER with ConLL-2002 dataset

C#命名规范中文版/C#编码规范中文版

Chinese NewsTitle Generation Project by GPT2.带有超级详细注释的中文GPT2新闻标题生成项目。

State of the art Chinese Word Segmentation with Bi-LSTMs

Develop input methods for Windows easily with Python and node.js

CLUE baseline pytorch CLUE的pytorch版本基线

An implementation of a full named-entity evaluation metrics based on SemEval'13 Task 9 - not at tag/token level but considering all the tokens that are part of the named-entity

An advanced guide to learn English that might benefit you a lot 🎉 . 可能是让你受益匪浅的英语进阶指南。

中文游戏服务器资源大全

📖《桌维网管实典》主机与程控终端信息安全运维，IT方向速成就业入职

Pytorch Implementation of "Adaptive Co-attention Network for Named Entity Recognition in Tweets" (AAAI 2018)

📙 中华新华字典数据库。包括歇后语，成语，词语，汉字。

a Fairseq fork for sequence tagging/labeling tasks

.NET Platform Architecture book (English, Chinese, Russian)

A language package for Minecraft Mods.

End-to-end neural relation extraction using deep biaffine attention (ECIR 2019)

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

Natural Language Toolkit for bahasa Malaysia, https://malaya.readthedocs.io/

CNN for Chinese Text Classification in Tensorflow

Named Entity Recognition based on dictionaries

这是一款基于web的通用文本标注工具，支持大规模实体标注、关系标注、事件标注、文本分类、基于字典匹配和正则匹配的自动标注以及用于实现归一化的标准名标注，同时也支持文本的迭代标注和实体的嵌套标注。标注规范可自定义且同类型任务中可“一次创建多次复用”。通过分级实体集合扩大了实体类型的规模，并设计了全新高效的标注方式，提升了用户体验和标注效率。此外，本工具增加了审核环节，可对多人的标注结果进行一致性检验和调整，提高了标注语料的准确率和可靠性。

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.

NEZHA: Neural Contextualized Representation for Chinese Language Understanding