sukeey's repositories
Conference-Accepted-Paper-List
Some Conferences' accepted paper lists (including AI, ML, Robotic)
generative-models
Generative Models by Stability AI
MetaTransformer
Meta-Transformer for Unified Multimodal Learning
CVPR2023-Papers-with-Code
CVPR 2023 论文和开源项目合集
Awesome-Multimodal-Large-Language-Models
:sparkles::sparkles:Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.
VisualGLM-6B
Chinese and English multimodal conversational language model | 多模态中英双语对话语言模型
tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
GMP
Generated Multimodal Prompt
gdown
Download a large file from Google Drive (curl/wget fails because of the security notice).
gpt4all
gpt4all: an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue
CBook-150K
中文图书语料MD5链接
paper-reading
深度学习经典、新论文逐段精读
W2NER
Source code for AAAI 2022 paper: Unified Named Entity Recognition as Word-Word Relation Classification
pytorch_bert_bilstm_crf_ner
基于pytorch的bert_bilstm_crf中文命名实体识别
ACOS
The datasets and code of ACL 2021 paper "Aspect-Category-Opinion-Sentiment Quadruple Extraction with Implicit Aspects and Opinions".
eznlp
Easy Natural Language Processing
SSEGCN-ABSA
SSEGCN: Syntactic and Semantic Enhanced Graph Convolutional Network for Aspect-based Sentiment Analysis
NLP_ability
总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力
evil.js
Use with caution
BERT-NER-Pytorch
Chinese NER(Named Entity Recognition) using BERT(Softmax, CRF, Span)
NLPDataSet
记录本人整理的一些数据集
CONTaiNER
Code for ACL 2022 paper "CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning"
Top-AI-Conferences-Paper-with-Code
This repository is a collection of AI top conferences papers (e.g. ACL, EMNLP, NAACL, COLING, AAAI, IJCAI, ICLR, NeurIPS, and ICML) with open resource code
Flat-Lattice-Transformer
code for ACL 2020 paper: FLAT: Chinese NER Using Flat-Lattice Transformer
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。
annotated_deep_learning_paper_implementations
🧑🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠