gokasiko's Stars
ZhuiyiTechnology/nl2sql_baseline
dice-group/AGDISTIS
AGDISTIS - Agnostic Named Entity Disambiguation
microsoft/IRNet
An algorithm for cross-domain NL2SQL
rubenIzquierdo/dbpedia_ner
Named Entity Recogniser (NER) and entity linker to dbpedia entries based on Dbpedia spotlight for KAF/NAF files.
gokasiko/transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
lizhe2004/chatbot-list
行业内关于智能客服、聊天机器人的应用和架构、算法分享和介绍
cuberite/cuberite
A lightweight, fast and extensible game server for Minecraft
google-research/tapas
End-to-end neural table-text understanding models.
rajammanabrolu/KG-DQN
zhusleep/pytorch_chinese_lm_pretrain
pytorch中文语言模型预训练
pkumod/CKBQA
A Chinese KBQA dataset with SPARQL annotations.
louisnino/RLcode
microsoft/rat-sql
A relation-aware semantic parsing model from English to SQL
xiefan-guo/CCKS2019_subject_extraction
CCKS2019面向金融领域的事件主体抽取
AlexYangLi/ccks2019_el
CCKS 2019 中文短文本实体链指比赛技术创新奖解决方案
ProHiryu/albert-chinese-ner
使用预训练语言模型ALBERT做中文NER
BDBC-KG-NLP/QA-Survey-CN
北京航空航天大学大数据高精尖中心自然语言处理研究团队开展了智能问答的研究与应用总结。包括基于知识图谱的问答(KBQA),基于文本的问答系统(TextQA),基于表格的问答系统(TableQA)、基于视觉的问答系统(VisualQA)和机器阅读理解(MRC)等,每类任务分别对学术界和工业界进行了相关总结。
BeHappyForMe/toy_translation
基于seq2seq + attention的小型英汉翻译NMT
wxzcyy/NMT
基于seq2seq的机器翻译模型
TingsongYu/PyTorch_Tutorial
《Pytorch模型训练实用教程》中配套代码
NoviScl/BERT-RACE
jiangxinyang227/bert-for-task
Nealcly/MuTual
A Dataset for Multi-Turn Dialogue Reasoning
joe817/Name-Disambiguation-Biendata-
2019 Biendata竞赛平台“OAG–WhoIsWho 同名消歧竞赛 赛道一”消歧比赛,第一名解决方案
wangbq18/Name-Disambiguation-Biendata-
2019 Biendata竞赛平台“OAG–WhoIsWho 同名消歧竞赛 赛道一”消歧比赛,第一名解决方案
BeHappyForMe/chinese-sequence-ner
chinese-sequence-ner多模型中文命名实体识别
ymcui/Chinese-BERT-wwm
Pre-Training with Whole Word Masking for Chinese BERT(中文BERT-wwm系列模型)
Determined22/zh-NER-TF
A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)
malllabiisc/EmbedKGQA
ACL 2020: Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings