Search Results for "compact" - Page 4
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Showing 732 open source projects for "compact"
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Porcupine
On-device wake word detection powered by deep learning
...Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening voice-enabled applications. It is using deep neural networks trained in real-world environments. Compact and computationally-efficient. It is perfect for IoT. Cross-platform. Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT. Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone. Android and iOS. Chrome, Safari, Firefox, and Edge. Linux (x86_64), macOS (x86_64, arm64), and Windows (x86_64). Scalable. It can detect multiple always-listening voice commands with no added runtime footprint. ... -
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VibeThinker
Diversity-driven optimization and large-model reasoning ability
VibeThinker is a compact but high-capability open-source language model released by WeiboAI (Sina AI Lab). It contains about 1.5 billion parameters, far smaller than many “frontier” models, yet it is explicitly optimized for reasoning, mathematics, and code generation tasks rather than general open-domain chat. The innovation lies in its training methodology: the team uses what they call the Spectrum-to-Signal Principle (SSP), where a first stage emphasizes diversity of reasoning paths (the “spectrum” phase) and a second stage uses reinforcement techniques (the “signal” phase) to refine toward correctness and strong reasoning. ... -
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Matplot++
Matplot++: A C++ Graphics Library for Data Visualization
...Matplot++ is a graphics library for data visualization that provides interactive plotting, means for exporting plots in high-quality formats for scientific publications, a compact syntax consistent with similar libraries, dozens of plot categories with specialized algorithms, multiple coding styles, and supports generic backends. -
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turbovec
A vector index built on TurboQuant, written in Rust with Python
...It is built around TurboQuant, a quantization approach designed to reduce vector storage while preserving useful distance information. The project targets workloads where embedding search needs to be compact, efficient, and practical to integrate into Python applications. It avoids a separate training phase for the quantizer, which can simplify setup compared with systems that require codebook learning. TurboVec is useful for developers building retrieval, ranking, semantic search, recommendation, or AI memory systems. Its main value is combining Rust performance with a Python-facing workflow for modern vector search experiments and applications. -
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101 FastAPI Tips
FastAPI Tips by The FastAPI Expert!
101 FastAPI Tips is a curated collection of practical FastAPI advice from a developer deeply involved in the FastAPI ecosystem. Rather than being a full framework or application template, it works as a compact learning resource for improving real FastAPI projects. The tips cover performance, async behavior, WebSocket patterns, project structure, dependency choices, testing habits, and production-minded design decisions. It is especially helpful for developers who already know the basics and want to avoid subtle mistakes that can hurt scalability, reliability, or maintainability. ... -
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ANTIRTOS
Function pointers queues classes library for Arduino
ANTIRTOS is a compact real-time operating system (RTOS) written in ANSI C for microcontrollers and embedded systems. It is designed to be simple, portable, and efficient, making it ideal for resource-constrained environments such as IoT devices, robotics, and educational hardware projects. ANTIRTOS features a basic scheduler, support for cooperative and preemptive multitasking, and offers portability across different CPU architectures with minimal changes. -
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Zeek
Zeek is a powerful network analysis framework
...Rather, Zeek sits on a “sensor,” a hardware, software, virtual, or cloud platform that quietly and unobtrusively observes network traffic. Zeek interprets what it sees and creates compact, high-fidelity transaction logs, file content, and fully customized output, suitable for manual review on disk or in a more analyst-friendly tool like a security and information event management (SIEM) system. -
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Bowtie 2
A fast and sensitive gapped read aligner
...It is especially effective for reads ranging from around 50 bases to hundreds or thousands of characters, and it supports modern sequencing workflows that require gapped, local, and paired-end alignment. The tool builds compact FM-index-based reference indexes, keeping memory usage low even for large genomes like the human genome. Bowtie 2 outputs alignments in SAM format and includes companion utilities for building and inspecting indexes. It is widely used in bioinformatics pipelines for RNA-seq, DNA-seq, metagenomics, variant analysis, and other sequencing-based research tasks. ... -
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BSON parser
BSON Parser for node and browser
...It provides encoding and decoding capabilities so JavaScript environments like Node.js and browsers can serialize rich data structures (including types not native to JSON) into the compact, efficient BSON binary representation used by MongoDB drivers and servers. Value types such as ObjectId, Binary, UTC datetime, Decimal128, and Long are provided as first-class objects, enabling precise representation of data that would otherwise be lossy or awkward in plain JSON. js-bson is designed for performance, with optimized algorithms for reading and writing binary data, minimizing overhead in database operations. ... -
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Airframe
Essential Building Blocks for Scala
Airframe is an essential building block for developing applications in Scala, including logging, object serialization using JSON or MessagePack, dependency injection, HTTP server/client with RPC support, functional testing with AirSpec, etc. Airframe RPC supports seamless integration of servers and clients using Scala as RPC interfaces. AirSpec is a simple unit testing framework for Scala and Scala.js. You can use public methods in your classes as test cases. There is no need to remember... -
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dots.ocr
Multilingual Document Layout Parsing in a Single Vision-Language Model
...The model is designed to recognize virtually any human script, making it highly effective for global and low-resource language scenarios. It achieves state-of-the-art performance on document parsing benchmarks while maintaining a relatively compact model size, demonstrating efficiency without sacrificing accuracy. Beyond standard OCR tasks, it extends its capabilities to parse complex visual elements such as charts, diagrams, and web interfaces, converting them into structured outputs like SVG code. -
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LongCat-Image
Foundation model for image generation
...Rather than relying on massive parameter counts typical of many cutting-edge models, LongCat-Image achieves strong photorealism, stable structure, and accurate bilingual (Chinese and English) text rendering with a more compact ~6-billion parameter architecture, making it competitive with much larger alternatives despite its relatively lean design. The model excels at both text-to-image generation and instruction-guided image editing, offering users versatile capabilities for creative and practical tasks—whether generating art, mockups, or adjusting existing visuals with fine control. -
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Magika
Fast and accurate AI powered file content types detection
Magika is an AI-powered file-type detector that uses a compact deep-learning model to classify binary and textual files with high accuracy and very low latency. The model is engineered to be only a few megabytes and to run quickly even on CPU-only systems, making it practical for desktop apps, servers, and security pipelines. Magika ships as a command-line tool and a library, providing drop-in detection that improves on traditional “magic number” and heuristic approaches, especially for ambiguous or short files. ... -
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litlyx
Analytics for developers, setup Analytics in 30 seconds
...This system is designed to provide a more thorough and eco-friendly way to clean glasses, lenses, and screens. The brand emphasizes sustainability by reducing single-use plastics and promoting long-term use of their products. Their cleaning kit is compact, portable, and designed to be effective for everyday use, ensuring that users can maintain clear vision without the hassle of disposable wipes or sprays. -
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Apache Avro
Apache Avro is a data serialization system
Apache Avro™ is a data serialization system. Simple integration with dynamic languages. Code generation is not required to read or write data files nor to use or implement RPC protocols. Code generation is an optional optimization, is only worth implementing for statically typed languages. Avro relies on schemas. When Avro data is read, the schema used when writing it is always present. This permits each datum to be written with no per-value overheads, making serialization both fast and... -
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Delaunator
Fast JavaScript library for Delaunay triangulation of 2D points
Delaunator is a fast library for Delaunay triangulation. It takes as input a set of points. The triangulation is represented as compact arrays of integers. It’s less convenient than other representations but is the reason the library is fast. After constructing a delaunay = Delaunator.from(points) object, it will have a triangles array and a halfedges array, both indexed by half-edge id. What’s a half-edge? A triangle edge may be shared with another triangle. Instead of thinking about each edge A↔︎B, we will use two half-edges A→B and B→A. ... -
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cheat.sh
The only cheat sheet you need
cheat.sh is a compact, network-accessible cheat-sheet service that serves concise examples and usage notes for hundreds of shell commands, programming languages, and tools via a simple HTTP interface. You can query it from the terminal (for example curl cht.sh/rsync or curl cheat.sh/ls) or browse the web front page; it also supports a shorthand hostname (cht.sh) and provides both online and standalone/local installation modes. -
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Kokoro
An inference library for Kokoro-82M
Kokoro is an open-weight text-to-speech model and inference library built around the lightweight Kokoro-82M model. It is designed to generate high-quality speech from text while staying fast, compact, and cost-efficient compared with larger TTS systems. The project is useful for developers who want deployable speech synthesis without depending on a closed platform. It can be installed as a Python package and used in applications, scripts, experiments, or production workflows. Kokoro’s Apache-licensed weights make it flexible for personal, research, and commercial use cases. ... -
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collapse
Advanced and Fast Data Transformation in R
...It operates on base R data structures like data frames and vectors and uses highly optimized C++ code under the hood to deliver significant speed improvements. collapse also includes tools for grouped operations, weighted statistics, and time series manipulation, making it a compact yet powerful utility for data scientists and researchers working in R. -
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tmux-mem-cpu-load
CPU, RAM, and load monitor for use with tmux
tmux-mem-cpu-load is a lightweight system monitoring utility designed for the tmux status line. It gives terminal users a compact way to view memory usage, CPU usage, and system load without opening a separate monitoring program. The tool is especially useful for developers, server administrators, and power users who spend long sessions inside tmux. It displays used and available memory in a concise format that fits naturally in a terminal status bar. It also shows CPU usage as a percentage and can include a small text-based usage graph. ... -
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SkillOpt
Text-space optimizer that trains reusable natural-language skills
SkillOpt is a Microsoft research project for improving frozen LLM agents by optimizing reusable natural-language skill documents. Instead of changing model weights, it treats a compact skill file as the trainable state of the agent. The system learns from agent rollouts, reflection, bounded edits, and validation gates to produce better instructions over time. Its output is a deployable best_skill.md artifact that can be reused across agent tasks. The project is focused on making agents more effective through text-space optimization rather than traditional fine-tuning. ... -
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pytudes
Python programs, usually short, of considerable difficulty
pytudes is Peter Norvig’s collection of short Python programs written to practice and demonstrate specific programming skills. The name is inspired by musical études, meaning compact exercises designed to build mastery through focused practice. The repository includes readable solutions, experiments, notebooks, and scripts that cover algorithms, puzzles, probability, search, language processing, simulation, and mathematical reasoning. It is useful for programmers who want to study elegant Python code while learning how experienced developers approach problem solving. ... -
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Cowboy
Small, fast, modern HTTP server for Erlang/OTP
Cowboy is a small, fast, modern HTTP server for Erlang and OTP applications. It provides a complete HTTP stack while keeping the codebase compact and optimized for low latency and low memory usage. Cowboy supports routing, request dispatching, HTTP handlers, REST handlers, WebSocket connections, and long-lived streaming-style interactions. Because it uses Ranch for connection management, it can be embedded directly inside larger Erlang systems rather than deployed only as a separate web server. ... -
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xkcptun
xkcptun is kcp tunnel for OpenWRT&LEDE, implemented in c language
...It also includes a spy utility, making the generated build more than a minimal two-binary tunnel setup. xkcptun can be built with CMake and supports static linking for easier deployment on constrained systems. It is most relevant to users who need a compact KCP tunnel implementation for routers, gateways, and custom network appliances. -
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LLM From Scratch
Build and train a GPT-style language model
...Instead of relying on high-level abstractions or prebuilt frameworks, the project walks users through implementing every core component manually, including tokenization, transformer architecture, training loops, and autoregressive text generation. The repository is intentionally simplified to focus on conceptual clarity, using a compact model of roughly 10 million parameters that can train on consumer hardware such as laptops within a relatively short time. Inspired by Andrej Karpathy’s nanoGPT, the project emphasizes learning through direct implementation and experimentation rather than black-box usage. The workshop documentation explains concepts such as self-attention, embeddings, gradient clipping, optimizer scheduling, and decoding strategies in a practical and approachable way.
