ljx's repositories
Anima
33B Chinese LLM, DPO QLORA, 100K context, AirLLM 70B inference with single 4GB GPU
anomaly-detection-resources
Anomaly detection related books, papers, videos, and toolboxes
awesome-annotation-tools
A curated list of awesome data annotation tools
awesome-relation-extraction
📖 A curated list of awesome resources dedicated to Relation Extraction, one of the most important tasks in Natural Language Processing (NLP).
bi-tempered-loss
Robust Bi-Tempered Logistic Loss Based on Bregman Divergences. https://arxiv.org/pdf/1906.03361.pdf
ccks2021-track2-code
“英特尔创新大师杯”深度学习挑战赛 赛道2：CCKS2021中文NLP地址要素解析
ChainKnowledgeGraph
ChainKnowledgeGraph, 产业链知识图谱包括A股上市公司、行业和产品共3类实体，包括上市公司所属行业关系、行业上级关系、产品上游原材料关系、产品下游产品关系、公司主营产品、产品小类共6大类。 上市公司4,654家，行业511个，产品95,559条、上游材料56,824条，上级行业480条，下游产品390条，产品小类52,937条，所属行业3,946条。
chinese-calendar
判断一天是不是法定节假日/法定工作日（查看节假日安排）
clinical-self-verification
Self-verification for LLMs.
ColossalAI
Making big AI models cheaper, easier, and scalable
FDU_KW_DEMI
DEMI入门练习
LLM-Agent-Paper-List
The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.
machine-learning-notes
My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接
MetaGPT
🌟 The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo
nlp-competitions-list-review
复盘所有NLP比赛的TOP方案，只关注NLP比赛，持续更新中！
Open-Assistant
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
OpenHowNet
Core Data of HowNet and OpenHowNet Python API
paper-reading
深度学习经典、新论文逐段精读
picard
PICARD - Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Models. PICARD is a ServiceNow Research project that was started at Element AI.
Spatio-temporal-Diffusion-Point-Processes
A diffusion-based framework for spatio-temporal point processes
Time-Series-Anomal-Detection
时间序列异常检测
tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.