Showing 121-140 of 563 projects
A Python library that provides various text embedding and similarity models, including Word2Vec, Sentence-BERT, and more.
An IoT solution library for embedded hardware, compatible with Arduino and ESP32 platforms.
This is a lightweight real-time operating system for embedded systems development.
A computer vision and sports analytics library for building sports-focused AI applications.
Lightweight, fast, and reliable key-value database engine in Go for high-throughput applications.
A small, portable AES128/192/256 encryption library in C for use in embedded systems and other constrained environments.
A collection of important graph embedding, classification and representation learning papers with implementations for vibe coders.
esProc SPL is a JVM-based programming language for structured data computation, serving as both a data analysis tool and an embedded computing engine.
AI-powered note-taking and knowledge management for developers, with intelligent connections and ChatGPT integration.
A blazing fast inference solution for text embeddings models built with Rust.
An ultra-lightweight, high-performance C/C++ logging library for embedded and IoT applications.
A JavaScript library for loading and processing images, with support for file metadata parsing and image manipulation.
Embedded JavaScript templates for Node.js, a popular templating engine for building web applications.
A community-driven platform to read and chat with AI bots powered by ChatGPT for developers.
A comprehensive guide for bare-metal programming on ARM microcontrollers, covering various hardware and software components.
An open-source, high-performance CNC milling controller written in C for Arduino boards.
A high-performance, AI-native database for LLM applications with hybrid search capabilities.
A simple framework for embedding Chromium-based browsers in other applications.
A small, event-driven TCP/IP stack written in Rust for embedded systems and low-level networking.
A comprehensive guide to using the RAG (Retrieval-Augmented Generation) technique for large language model applications.
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