Name: Jianing Wang
Type: User
Company: ECNU / UC San Diego
Bio: I am Jianing Wang, the founder of @HugAILab , a Ph.D. student from East China Normal University in Shanghai. My research field is NLP and Knowledge Graph.
Location: San Diego, CA
Blog: https://wjn1996.github.io/
Jianing Wang's Projects
2020年-2021年 讨论班ppt
农业知识图谱(AgriKG)：农业领域的信息检索，命名实体识别，关系抽取，智能问答，辅助决策
A PyTorch implementation of the Transformer model in "Attention is All You Need".
This repo is our research summary and playground for MRC. More features are coming.
中文医疗信息处理基准CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
基于ChatGLM2-6B进行微调，包括全参数、参数有效性、量化感知训练等，可实现指令微调、多轮对话微调等。
Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）
中文医疗NLP领域 数据集，论文 ，知识图谱，语料，工具包
Chinese Biomedical Language Understanding Evaluation benchmark (ChineseBLUE)
CoLAKE: Contextualized Language and Knowledge Embedding
Code for our ACL 2021 paper - ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer
数据科学与工程算法基础实践课——基于矩阵分解的推荐系统
A paper list of object detection using deep learning.
Example models using DeepSpeed
The recent Distant Supervision Relation Extraction paper lists. We have list all the DSRE paper from 2009 to 2020
EasyNLP: An Easy-to-use NLP Toolkit
EasyTransfer is designed to make the development of transfer learning in NLP applications easier.
Code and data of ACL 2021 paper "Few-NERD: A Few-shot Named Entity Recognition Dataset"
华师大开源设计与开发课程期末作业
:zap: Dynamically generated stats for your github readmes
中文分词 词性标注 命名实体识别 依存句法分析 语义依存分析 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理
HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!😊
HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!😊 HugNLP will released to @HugAILab
A framework to empover LLMs on graph reasoning and generation. Refer to our paper: https://arxiv.org/pdf/2402.08785.pdf
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent