Zado-Tan

Zado-Tan's Stars

• FlagOpen/FlagEmbedding

  Retrieval and Retrieval-augmented LLMs

  Language:Python8.1k591

• hpcaitech/ColossalAI

  Making large AI models cheaper, faster and more accessible

  Language:Python39k4.3k

• PaddlePaddle/ERNIE

  Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.

  Language:Python6.3k1.3k

• xialeiliu/Awesome-Incremental-Learning

  Awesome Incremental Learning

  3.9k579

• TAdeJong/beamer-universiteit-leiden

  An unofficial LaTeX beamer template for scientific presentations in Universiteit Leiden layout

  Language:TeX124

• AntNLP/undergraduates-seminar

  seminar for undergraduates

  Language:Python154

• fordai/CCKS2019-Chinese-Clinical-NER

  The word2vec-BiLSTM-CRF model for CCKS2019 Chinese clinical named entity recognition.

  Language:Python7515

• qiufengyuyi/event_extraction

  baidu aistudio event extraction competition

  Language:Python22539

• ShannonAI/Entity-Relation-As-Multi-Turn-QA

  Code for ACL 2019 : Entity-Relation Extraction as Multi-Turn Question Answering

  Language:Python7327

• ymcui/Chinese-BERT-wwm

  Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）

  Language:Python9.8k1.4k

• graykode/nlp-roadmap

  ROADMAP(Mind Map) and KEYWORD for students those who have interest in learning NLP

  3.2k515

• pjreddie/darknet

  Convolutional Neural Networks

  Language:C25.9k21.3k

• Determined22/zh-NER-TF

  A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)

  Language:Python2.3k937

• MenglinLu/Chinese-clinical-NER

  CCKS2019中文命名实体识别任务。从医疗文本中识别疾病和诊断、解剖部位、影像检查、实验室检验、手术和药物6种命名实体。现已实现基于jieba和AC自动机的baseline构建、基于BiLSTM和CRF的序列标住模型构建。bert的部分代码主要源于https://github.com/charles9n/bert-sklearn.git 感谢作者。 模型最终测试集得分0.81，还有较大改进空间。可以当做一个baseline。

  Language:Python35076

• Jekub/Wapiti

  A simple and fast discriminative sequence labeling toolkit ( http://wapiti.limsi.fr )

  Language:C25186

• kyzhouhzau/NLPGNN

  1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.

  Language:Python33265

• AntNLP/seminar

  antnlp seminar materials

  8541

• StephanieWyt/NMN

  Source code and datasets for ACL 2020 paper: Neighborhood Matching Network for Entity Alignment.

  Language:Python7517

• 7ZFNLP/Knowledge-Analysis-and-Processing-2020Fall

  2020知识处理与分析课程资料

  1

• graphdeeplearning/benchmarking-gnns

  Repository for benchmarking graph neural networks

  Language:Jupyter Notebook2.5k454