There are 76 repositories under question-answering topic.
AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP
SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.
An open source library for deep learning end-to-end dialog systems and chatbots.
Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
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
State of the Art Natural Language Processing
AdalFlow: The library to build & auto-optimize LLM applications.
OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.
Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
The Self-Coding System for Your App — Alan AI SDK for Web
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
Self-contained Machine Learning and Natural Language Processing library in Go
Datasets, SOTA results of every fields of Chinese NLP
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。
A collection of research on knowledge graphs
:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.
NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego
Awesome & Marvelous Amas
knowledge graph知识图谱,从零开始构建知识图谱
📙 PHP 面试知识点汇总
End-to-end neural table-text understanding models.
🔎 Search the information available on a webpage using natural language instead of an exact string match.
:helicopter: 保险行业语料库,聊天机器人
Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN
A central, open resource for data and tools related to chain-of-thought reasoning in large language models. Developed @ Samwald research group: https://samwald.info/
Question generation using state-of-the-art Natural Language Processing algorithms
Learn about Machine Learning and Artificial Intelligence
A list of recent papers about Graph Neural Network methods applied in NLP areas.
ChatGPT 中文语料库 对话语料 小说语料 客服语料 用于训练大模型