large-language-models

This is the repository for the Tool Learning survey.

MindSpore online courses: Step into LLM

Prompt Decorators are structured prefixes, such as +++Reasoning and +++StepByStep, designed to enhance AI responses. Inspired by Python decorators, they make AI outputs more logical, accurate, and well-organized without requiring lengthy instructions, simplifying interactions for users.

Interpretability for sequence generation models 🐛 🔍

Enhance your résumé with Large Language Models

A highly efficient, secure, and stable application development platform with excellent performance, easy scalability, and deep integration of AI capabilities such as LLM, AI Chat, RAG, and Agents.高效、安全、稳定的服务研发平台，具备良好性能，同时易扩展，深度集成LLM、AIChat、RAG、Agent等AI能力

[WWWJ 2024] LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities

🌿孙思邈中文医疗大模型(Sunsimiao)：提供安全、可靠、普惠的中文医疗大模型

🚀 Retrieval Augmented Generation (RAG) with txtai. Combine search and LLMs to find insights with your own data.

Resource, Evaluation and Detection Papers for ChatGPT

🦋 Production grade chaining engine behind TuneChat. Self host today!

Run Effective Large Batch Contrastive Learning Beyond GPU/TPU Memory Constraint

A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch

Your First LLM-Wiki Conversation Knowledge Base

LLMs and Machine Learning done easily

Govern & Secure your AI

A curated list of retrieval-augmented generation (RAG) in large language models

大模型多维度中文对齐评测基准 (ACL 2024)

The official code repository supporting the book, Grokking Artificial Intelligence Algorithms

Redis Vector Library (RedisVL) -- the AI-native Python client for Redis.