Lists (8)
Sort Name ascending (A-Z)
Stars
📚 Freely available programming books
📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
A feature-rich command-line audio/video downloader
Build AI agents from first principles using a local LLM - no frameworks, no cloud APIs, no hidden reasoning.
Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.
HTML PPT Studio — AgentSkill with 24 themes, 31 layouts, 20+ animations for building professional HTML presentations
A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Grok Build & Hermes Agent. Only official website: ccswitch.io
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs (Qwen3.6, DeepSeek-V4, GLM-5.1, InternLM3, Llama4, ...) and 300+ MLLMs (Qwen3-VL, Qwen3-Omni, InternVL3.5, Ovis2.5, GLM4.5v, Gemma4, Llava, …
LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing …
数字生命卡兹克开源的 AI Skills 合集 | Agent Skills: neat-freak 洁癖 (docs/memory closeout), hv-analysis, khazix-writer & more — Claude Code, Codex & 40+ agents
Speech to text (PocketSphinx, Iflytex API, Baidu API) and text to speech (pyttsx3) | 语音转文字(PocketSphinx、百度 API、科大讯飞 API)和文字转语音(pyttsx3)
Academic Research Skills for Claude Code: research → write → review → revise → finalize
🧠「大模型」2小时完全从0训练64M的小参数LLM!Train a 64M-parameter LLM from scratch in just 2h!
本项目是一个面向小白开发者的大模型应用开发教程,在线阅读地址:https://datawhalechina.github.io/llm-universe/
推荐系统入门教程,在线阅读地址:https://datawhalechina.github.io/fun-rec/
🔍大模型应用开发实战一:RAG 技术全栈指南,在线阅读地址:https://datawhalechina.github.io/all-in-rag/
An extremely fast Python package and project manager, written in Rust.
LangChain 教程 - LLM/Function Call/MCP/Skill/Agent/Multi-Agent/Threading
It will be revised soon.
The new Windows Terminal and the original Windows console host, all in the same place!
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调(全参数/Lora)、部署国内外开源大模型(LLM)/多模态大模型(MLLM)教程