Search Results for "memory" - Page 28
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Showing 2497 open source projects for "memory"
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shimmy
Python-free Rust inference server
...This compatibility enables developers to replace remote AI services with locally hosted models while keeping their existing software architecture intact. Shimmy focuses on performance and simplicity, using efficient runtime components to minimize memory usage and startup time compared to heavier inference frameworks. It supports modern model formats such as GGUF and SafeTensors and can automatically discover models stored locally or in common directories used by other AI tools. Advanced capabilities include CPU offloading for Mixture-of-Experts models and GPU acceleration, enabling large models to run on consumer hardware with limited VRAM. -
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Intel LLM Library for PyTorch
Accelerate local LLM inference and finetuning
...The framework provides hardware-aware optimizations and low-precision computation techniques that significantly improve the performance of large language models while reducing memory consumption. IPEX-LLM supports a wide range of popular models, including architectures such as LLaMA, Mistral, Qwen, and other transformer-based systems. The library can integrate with common AI frameworks and serving tools such as Hugging Face Transformers, LangChain, and vLLM, allowing developers to incorporate optimized inference into existing pipelines. -
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LangChain for Java
LangChain4j is an open-source Java library
LangChain for Java is an open-source Java framework designed to simplify the development of applications powered by large language models. The library provides a unified API that allows developers to connect Java applications to multiple AI providers and embedding databases without having to implement separate integrations for each service. Its architecture includes abstractions for prompts, chat interactions, document processing, embeddings, and vector storage, enabling developers to build... -
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Hanami
A flexible framework for maintainable Ruby apps
Hanami is a modern Ruby web framework that aims to be lightweight, fast, and modular, in contrast to the monolithic design of Rails. It emphasizes separation of concerns, encouraging developers to structure applications into clear layers of controllers, views, entities, and repositories. Each component—like the router, model layer, or view rendering engine—can be used independently, which gives developers flexibility to build lean applications. Hanami promotes immutability, plain old Ruby... -
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Ruma
A set of Rust crates for interacting with the Matrix chat network
...Learn more in the Introduction to Matrix. Rust is a systems programming language from Mozilla built with safety, concurrency, and performance in mind. Its novel approach to memory safety and its rich type system make it an excellent choice for writing fast, secure, and reliable programs. -
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Authelia
The Single Sign-On Multi-Factor portal for web apps
Authelia is an open-source authentication and authorization server and portal fulfilling the identity and access management (IAM) role of information security in providing multi-factor authentication and single sign-on (SSO) for your applications via a web portal. It acts as a companion for common reverse proxies. With a compressed container size smaller than 20 megabytes and observed memory usage normally under 30 megabytes, it's one of the most lightweight solutions available. Written in Go and React, authorization policies and many other backend tasks are completed in mere milliseconds and login portal loading times of 100 milliseconds makes it one of the fastest solutions available. Processors can use a lot of electricity, but when idle usage is basically so low that you can't measure it, and active usage in a small business environment being under 1% you can rest easy (with the exclusion of password hashing). -
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plow
A high-performance HTTP benchmarking tool
...It can run for a set duration( option -d), for a fixed number of requests(option -n), or until Ctrl-C is interrupted. The implementation of real-time computing Histograms and Quantiles using stream-based algorithms inspired by Prometheus with low memory and CPU bounds. so it's almost no additional performance overhead for benchmarking. -
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RIBs
Uber's cross-platform mobile architecture framework
...Plus, most RIB logic is decoupled from child RIB logic. This makes RIB classes easy to test and reason about independently. Tooling for developer productivity. RIBs come with IDE tooling around code generation, memory leak detection, static analysis and runtime integrations. -
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DenchClaw
Fully Managed OpenClaw Framework for all knowledge work ever
DenchClaw is a local-first AI-powered CRM and productivity platform built on top of the OpenClaw framework, designed to transform a user’s entire computer into a programmable, agent-driven workspace. Unlike traditional cloud-based CRMs or AI tools, it runs entirely on the user’s machine and exposes a web interface locally, allowing full control over data, workflows, and automation without relying on external servers. The system combines database management, browser automation, and AI... -
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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... -
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Live-Forensicator
A suite of Tools to aid Incidence Response and Live Forensics
Live-Forensicator is a toolkit intended for live forensic collection and initial triage on Windows machines. It automates the capture of volatile information—running processes, network connections, loaded drivers, account sessions, and in-memory artifacts—into a consistent artifact set that investigators can analyze offline. The tool tries to be non-invasive while collecting sensitive data quickly and logs the collection steps to preserve chain-of-custody details and to help auditors understand potential collection side effects. Because live collection can alter system state, Live-Forensicator includes options to limit intrusive actions and to capture hashes, timestamps, and provenance metadata to aid later validation. ... -
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react-native-fast-tflite
High-performance TensorFlow Lite library for React Native
react-native-fast-tflite is a high-performance TensorFlow Lite library for React Native applications. It is built with Nitro Modules and uses the low-level C and C++ TensorFlow Lite core API for direct memory access. The library supports zero-copy ArrayBuffers, which helps reduce overhead when passing model inputs and outputs through React Native. It can load and swap TensorFlow Lite models at runtime, making it useful for apps that run multiple machine learning tasks. The project supports GPU-accelerated delegates such as CoreML, Metal, and OpenGL. ... -
13
Libdragon
Open source library for N64 development
...The library provides both low-level access to hardware and higher-level abstractions for graphics, audio, and input handling. It supports advanced features such as accelerated 2D rendering and efficient memory management tailored to the N64 architecture. Developers can test builds on emulators or real hardware using flash cartridges. The project is designed to modernize N64 development while maintaining compatibility with the console’s original capabilities. Overall, it serves as a complete and modern environment for retro game development. -
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sectorlisp
Bootstrapping LISP in a Boot Sector
The sectorlisp project is a minimal implementation of the Lisp programming language designed to fit within extremely constrained environments. It is engineered to run in very small memory footprints, making it suitable for educational purposes and experimentation with low-level programming concepts. The project demonstrates how a functional programming language can be implemented with minimal resources while still retaining core features. It focuses on simplicity, providing a stripped-down interpreter that highlights the fundamental principles of Lisp. ... -
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Watlings
Learn WebAssembly by writing small programs
...Inspired by projects like Rustlings, it provides a collection of small, focused challenges that help users understand how WebAssembly works at a low level, including instructions, memory management, and control flow. Each exercise presents partially completed code that the user must fix or complete, reinforcing learning through hands-on problem solving rather than passive reading. The platform runs entirely in the browser, allowing users to experiment with WAT code and see immediate results without installing any tools. ... -
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Flash-MoE
Running a big model on a small laptop
Flash-MoE is a high-performance implementation of mixture-of-experts (MoE) architectures designed to optimize the efficiency and scalability of large AI models. It focuses on accelerating routing and computation by leveraging optimized kernels and memory management techniques, allowing models to dynamically select specialized sub-networks during inference. The project aims to reduce the computational cost typically associated with MoE systems while maintaining or improving performance. It likely includes support for GPU acceleration and parallel processing, enabling it to handle large-scale workloads effectively. ... -
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autoresearch-mlx
Apple Silicon (MLX) port of Karpathy's autoresearch
...It maintains the core autoresearch structure, where an AI agent iteratively edits a training script, executes experiments under a fixed time budget, and evaluates results based on a defined metric such as validation bits per byte. The system is tailored for Apple hardware, leveraging unified memory and MLX capabilities to achieve efficient training on Mac devices. It includes a minimal and focused project structure consisting of data preparation utilities, a modifiable training file, and a program specification that governs the agent’s behavior. The framework logs experiment results and supports continuous iteration, enabling long-running optimization cycles that can reveal hardware-specific performance patterns. -
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Attention Residuals (AttnRes)
Drop-in replacement for standard residual connections in Transformers
Attention Residuals is a research-driven architectural innovation for transformer-based models that replaces traditional residual connections with an attention-based mechanism to improve information flow across layers. In standard transformers, residual connections simply sum outputs from previous layers, which can lead to uncontrolled growth of hidden states and dilution of early-layer information in deep networks. Attention Residuals introduces a learnable softmax attention mechanism that... -
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NVIDIA Model Optimizer
A unified library of SOTA model optimization techniques
Model Optimizer is a unified library that provides state-of-the-art techniques for compressing and optimizing deep learning models to improve inference efficiency and deployment performance. It brings together multiple optimization strategies such as quantization, pruning, distillation, and speculative decoding into a single cohesive framework. The library is designed to reduce model size and computational requirements while maintaining accuracy, making it particularly valuable for deploying... -
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AgentGuide
AI Agent Development Guide, LangGraph in Action, Advanced RAG
...Instead of presenting scattered resources, the repository organizes them into a systematic learning roadmap that guides learners from foundational concepts to advanced AI agent systems. The guide covers topics such as agent frameworks, retrieval-augmented generation systems, multi-agent collaboration, memory management, and tool usage. It also includes practical projects, interview preparation materials, and curated research papers related to AI agents and LLM engineering. The project is designed not only for learning but also for career preparation, helping developers understand how to build portfolio projects and prepare for AI engineering roles. -
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AgentScope Java
Agent-Oriented Programming for Building LLM Applications
...It also supports human-in-the-loop intervention, allowing developers or users to inject guidance at any point during reasoning while preserving state and tool context. Built with enterprise needs in mind, AgentScope Java integrates into traditional Java stacks and provides structured abstractions for memory, workflows, and tool invocation. -
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Zen C
Write like a high-level language, run like C
...Zen-C includes a lightweight compiler front-end and runtime that can target multiple platforms, enabling users to compile and run code on both desktop and embedded environments without heavy tooling. Because it prioritizes clarity and predictability, the language makes it easier for learners to understand core systems concepts while still accessing low-level memory control and performance. -
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Resources-Front-End-Beginner
The most essential list of resources for Front-End beginners
...It organizes learning links across topics like HTML, CSS, JavaScript, Git, tooling, and practice projects, making it easy to chart a study path. The repository balances conceptual resources with hands-on tutorials and challenges so learners can build muscle memory. It also highlights community spaces and reference material to encourage collaboration and long-term growth. Clear signposting and simple emoji markers help readers gauge difficulty and format at a glance. Beginner friendliness is the core goal, lowering friction for first contributions and steady skill progression. -
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jstraining
Training materials designed to teach JavaScript
...It can be adapted for short bootcamps, brown-bag sessions, or self-guided study. Instructors benefit from ready-to-use outlines, while learners get runnable code and tasks that build muscle memory. -
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SYSADMIN Test Questions
A collection of Linux Sysadmin Test Questions and Answers
...It spans fundamentals like filesystems, permissions, processes, and networking, then ventures into security, performance, virtualization, containers, and databases. The format encourages quick drills: pick a topic, answer from memory, then compare against concise explanations. Many questions highlight real-world troubleshooting patterns rather than purely theoretical trivia, reflecting what admins face daily. As an interview prep resource, it helps candidates assess breadth and identify weak spots before deeper study. For teams, it doubles as a training checklist to standardize baseline knowledge across junior and mid-level engineers.
