AI 开源项目榜。

Pytorch implementation of "Fully-Convolutional Siamese Networks for Object Tracking"

Open-Source Toolkit for End-to-End Korean Automatic Speech Recognition leveraging PyTorch and Hydra.

[ICLR 2025, Oral] EmbodiedSAM: Online Segment Any 3D Thing in Real Time

Make Every Hardware Intelligent — an open-source Agent OS for hardware intelligence

MCP server to deploy apps to Cloud Run

🔥3D点云目标检测&语义分割(深度学习)-SOTA方法,代码,论文,数据集等

一个计算机视觉、机器学习与深度学习相关的项目，看课程的笔记还有自己做的程序

Large model-assisted paper review

[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen

👁️ + 💬 + 🎧 = 🤖 Curated list of top foundation and multimodal models! [Paper + Code + Examples + Tutorials]

YOLO v3 物体检测算法

A one-stop repository for low-code easily-installable object detection pipelines.

An experimental platform for federated learning.

Here is a pytorch implementation of deeplabv3+ supporting ResNet(79.155%) and Xception(79.945%). Multi-scale & flip test and COCO dataset interface has been finished.

Qwen DianJin: LLMs for the Financial Industry by Alibaba Cloud（通义点金：阿里云金融大模型）

Transformer Tracking (CVPR2021)

Community fetch recipes for bb-browser — pre-built adapters for Reddit, Twitter, GitHub, and more

Natural language browser automation

kubectl for AI Agents

Embedded agents your customers use to automate work, build views, and connect their tools.

A pre-built agent for TableGPT2.

Microsoft Automatic Mixed Precision Library

Bring any model to Codex, assign them any role, use them in /goal or any workflow.

[ICML 2024] TrustLLM: LLM trustworthiness evaluation across truthfulness, safety, fairness, robustness, privacy and ethics. Python/CLI toolkit for local models, compatible APIs and AI agent orchestration.

Code for the book Deep Learning From Scratch, from O'Reilly September 2019

By a 12-year product manager who builds 0-to-1: takes a beginner from a vague idea to a buildable plan, then guides the build (GitHub basics, clean-code habits, a verify-and-iterate loop, a checkup for the mess). For Claude Code, Codex, and Antigravity. grill-me is for engineers, vibe-check is for everyone else.

A better /goal

本教程将全面指导你如何快速搭建自己的AI应用环境，从Docker桌面版的安装与配置开始，到本地部署Dify并自定义AI助手功能，让你轻松实现“猜病例”、“甜蜜哄人”、“新生入学指南”、“小红书读书卡片”与“面试宝典”等多种特色AI应用。并教会你从基础智能体到使用工作流，再到知识库、DeepResearch、数据库、MCP、复杂任务编排等高阶任务，由浅到深的学习掌握基于dify的大模型应用开发。