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100-days-of-ml-code

100-Days-Of-ML-Code中文版

accelerate

🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision

accelerate-deepspeed-test

Testing DeepSpeed integration in 🤗 Accelerate

ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

algorithms

常用算法的 C++ 实现

android

awesome-chinese-llm

整理开源的中文大语言模型，以规模较小、可私有化部署、训练成本较低的模型为主，包括底座模型，垂直领域微调及应用，数据集与教程等。

awesome-cpp-cn

C++ 资源大全中文版，标准库、Web应用框架、人工智能、数据库、图片处理、机器学习、日志、代码分析等

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

beautifulsoup

Git Clone of Beautiful Soup (https://code.launchpad.net/~leonardr/beautifulsoup/bs4)

betterdl

bigdata-notes

大数据入门指南 :star:

bootstrap

The most popular HTML, CSS, and JavaScript framework for developing responsive, mobile first projects on the web.

breeze

一个C++的轻量级的分布式服务器引擎, 架构**为一切皆service.

brook

Brook is a cross-platform(Linux/MacOS/Windows/Android/iOS) proxy/vpn software

c270_camer

caffe

Caffe: a fast open framework for deep learning.

chinese-llama-2-7b

开源社区第一个能下载、能运行的中文 LLaMA2 模型！

chinese-llama-alpaca

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

chinese-llama-alpaca-3

中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3

clash-for-windows_chinese

clash for windows汉化版. 提供clash for windows的汉化版, 汉化补丁及汉化版安装程序

cmake-demo

《CMake入门实战》源码

consistent-hashing

dataminingalgorithm

数据挖掘18大算法实现以及其他相关经典DM算法

daze

Daze is a tool to help you link to the Internet.

deep-learning-with-tensorflow-book

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

deeplearning

深度学习入门教程, 优秀文章, Deep Learning Tutorial

deeplearningwithme

《跟我一起深度学习》

digital_video_introduction

A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding).

docker-llama2-chat

Play LLaMA2 (official / 中文版 / INT4 / llama2.cpp) Together! ONLY 3 STEPS! ( non GPU / 5GB vRAM / 8~14GB vRAM)