“连续八年成为全世界最受喜爱的语言，无 GC 也无需手动内存管理、极高的性能和安全性、过程/OO/函数式编程、优秀的包管理、JS 未来基石" — 工作之余的第二语言来试试 Rust 吧。本书拥有全面且深入的讲解、生动贴切的示例、德芙般丝滑的内容，这可能是目前最用心的 Rust 中文学习教程 / Book

A third-party, open-source ProtonMail CardDAV, IMAP and SMTP bridge

✉️ A streaming Go library for the Internet Message Format and mail messages

📤 An SMTP client & server library written in Go

LLVM IR入门指南

Monkey Lang using ANTLR4 parser

The Fast Lexical Analyzer - scanner generator for lexing in C and C++

Currently extending the Monkey programming language designed in the books "Writing An Interpreter In Go" and "Writing a Compiler in Go"

Monkey Programming Language written in Rust.

The Go programming language

The Wa Programming Language

📚 µGo语言实现(从头开发一个迷你Go语言编译器)

📚 《Go语言定制指南》(原名：Go语法树入门/开源免费图书/Go语言进阶/掌握抽象语法树/Go语言AST)

Empowering everyone to build reliable and efficient software.

The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.

Documentation on how to use the Rust Programming Language to develop firmware for bare metal (microcontroller) devices

📚 Learn to write an embedded OS in Rust 🦀

Denoising Diffusion Probabilistic Models

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Fast and memory-efficient exact attention

Official repo for consistency models.

Locally run an Instruction-Tuned Chat-Style LLM

The simplest way to run Alpaca (and other LLaMA-based local LLMs) on your own computer

ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型

4 bits quantization of LLaMA using GPTQ

记录GitHub热门仓库，每小时更新，按天归档。

the AI-native open-source embedding database

Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"