You Zhang's repositories
ecco
Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).
SoftWareDesign_2023Summer
软件设计与开发作业说明
DG_RRR
Repository of Domain Generalization via Switch Knowledge Distillation for Robust Review Representation
Attribute-based-LN
The repo for AI-Transformer.
LMD
Code of Layerwised Multimodal Knowledge Distillation for Vision-Language Pretrained Model
federated-distillation
The code for Heterogeneous Federated Distillation with Mutual Information Maximization
awesome-pretrained-chinese-nlp-models
Awesome Pretrained Chinese NLP Models,高质量中文预训练模型集合
semeval22_structured_sentiment
SemEval-2022 Shared Task 10: Structured Sentiment Analysis
BertForMaskedLM-Performance
BERT MLM 성능 체크
Awesome-CV
:page_facing_up: Awesome CV is LaTeX template for your outstanding job application
Deep-Learning-with-TensorFlow-book
深度学习入门开源书,基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
Conciseness
Conciseness is Better: Recurrent Attention LSTM Model for Document-Level Sentiment Analysis
free-programming-books
:books: Freely available programming books
SciencePlots
Matplotlib styles for scientific plotting
CrossNER
CrossNER: Evaluating Cross-Domain Named Entity Recognition (AAAI-2021)
BilinearReview_journal
Personalized Sentiment Classification of Customer Reviews via an Interactive Attributes Attention Model
TH-CPL
清华大学计算机学科推荐学术会议和期刊列表
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
awesome-knowledge-graph
整理知识图谱相关学习资料
EMNLP_2020_datasets
All datasets in experiments used in the proposed paper
lihang-code
《统计学习方法》的代码实现
leeml-notes
李宏毅《机器学习》笔记,在线阅读地址:https://datawhalechina.github.io/leeml-notes
Dive-into-DL-PyTorch
本项目将《动手学深度学习》原书中的MXNet代码实现改为PyTorch实现。
d2l-pytorch
This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.
Deep-Learning-with-PyTorch-Tutorials
深度学习与PyTorch入门实战视频教程 配套源代码和PPT