Stars
KITTI Object Detection with Distance Prediction
Drogon: A C++14/17/20 based HTTP web application framework running on Linux/macOS/Unix/Windows
The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.
Apollo notes (Apollo学习笔记) - Apollo learning notes for beginners.
🤗 LeRobot: Making AI for Robotics more accessible with end-to-end learning
using single camera to measure the distance opencv python,
🚀🚀 「大模型」2小时完全从0训练26M的小参数GPT！🌏 Train a 26M-parameter GPT from scratch in just 2h!
AI Agent + Coding Agent + 300+ assistants: agentic AI desktop with autonomous coding, intelligent automation, and unified access to frontier LLMs.
Compute time-to-collision (TTC) using Lidar and Camera sensors. Identify suitable keypoint detector-descriptor combinations for TTC estimation.
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
Awesome Knowledge Distillation
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Implementation for PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
High-performance In-browser LLM Inference Engine
全面ESM+Vue3+Vite+Element-Plus+TypeScript编写的一款后台管理系统（兼容移动端）
🔥🔥🔥BaseDemo 是Android MVVM + Retrofit + OkHttp + Coroutine 协程 + Room + 组件化架构的Android应用开发规范化架构，通过不断的升级迭代，目前主要分为两个版本，分别为分支 MVVM+Databinding 组件化版本，分支MVVM+Databinding+Single 单体版本。旨在帮助您快速构建属于自己的APP项目架构，做…
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
收录NLP竞赛策略实现、各任务baseline、相关竞赛经验贴（当前赛事、往期赛事、训练赛）、NLP会议时间、常用自媒体、GPU推荐等，持续更新中
综合性网络质量(PING)检测工具，支持正/反向PING绘图、互PING拓扑绘图与报警、全国PING延迟地图与在线检测工具等功能
JavaMelody : monitoring of JavaEE applications
Unified monitoring wallboard — Light, ergonomic and reliable monitoring for anything.
Machine Learning Yearning 中文版 - 《机器学习训练秘籍》 - Andrew Ng 著