Stars
微信机器人，可接入DeepSeek、Gemini、ChatGPT、ChatGLM、讯飞星火、Tigerbot等大模型。微信 hook WeChat Robot Hook.
NJUSE-专业课 LFS配额已经超支，可能已经无法继续contribute
一个基于✨HOOK机制的微信机器人，支持🌱安全新闻定时推送【FreeBuf，先知，安全客，奇安信攻防社区】，👯Kfc文案，⚡漏洞查询，⚡手机号归属地查询，⚡知识库查询，🎉星座查询，⚡天气查询，🌱摸鱼日历，⚡微步威胁情报查询， 🐛视频，⚡图片，👯帮助菜单。📫 支持积分功能，⚡支持自动拉人，，🌱自动群发，👯Ai回复（国内主流AI模型，扣子，FastGpt，Dify全面支持！），⚡视频号解析，😄自…
Up-to-date simple useragent faker with real world database
从零编写游戏引擎教程 Writing a game engine tutorial from scratch
A central hub for gathering and showcasing amazing projects that extend OpenMMLab with SAM and other exciting features.
[Open-Source Project] Combining MMOCR with Segment Anything & Stable Diffusion. Automatically detect, recognize and segment text instances, with serval downstream tasks, e.g., Text Removal and Text…
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM …
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
[NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"
PyTorch code and models for the DINOv2 self-supervised learning method.
[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
Official implementation of "Segment Any Anomaly without Training via Hybrid Prompt Regularization (SAA+)".
自己整理了一些网上和书籍中的知识与笔记，来应对技术面试可能遇到的一些问题，包括算法、操作系统、计算机网络、Java、C++、Python、Go。概念不是最重要的！概念不是最重要的！概念不是最重要的！练习题才是！重要的事情说三遍，概念是不是看了很多遍，看几遍忘几遍，题目做过几遍，是不是印象很深，精华是题目，笔者在大量练习后摘录了书籍、牛客网、赛码网、W3C、CSDN等各种渠道的练习题，较为基础…
最全面的游戏开发技术图谱(Game Development Map)。帮助游戏开发者们在已知问题上节省时间，省出更多的精力投入到更有创造性的工作中去。
A bran-new League of Legends assistant software, a replacement for WeGame.
Chinese version of GPT2 training code, using BERT tokenizer.
Model parallel transformers in JAX and Haiku
Home of CodeT5: Open Code LLMs for Code Understanding and Generation
This is an attempt to use transformers and self attention in order to convert English descriptions into Python code.
Example code for the book "Thinking in Java, 4th Edition"
📚 本代码库是作者小傅哥多年从事一线互联网 Java 开发的学习历程技术汇总，旨在为大家提供一个清晰详细的学习教程，侧重点更倾向编写Java核心内容。如果本仓库能为您提供帮助，请给予支持(关注、点赞、分享)！
The source code from the third edition of Effective Java, with minor additions as necessary to make it runnable.