Foundry-Local هي أداة تطوير للتعلم الآلي مصممة لتسهيل الاستدلال الخاص على الجهاز وإدارة النماذج. توفر بيئة خادم محلية تستضيف نماذج التعلم الآلي مباشرة على أجهزة المستخدم، مما يضمن بقاء جميع عمليات معالجة البيانات، بما في ذلك معالجة المطالبات وتحويل الكلام إلى نص، داخل البيئة المحلية دون الحاجة إلى اتصال سحابي خارجي.
الميزات الرئيسية لـ microsoft/foundry-local هي: Local Model Execution, Machine Learning Model APIs, Local AI Inference, Local LLM API Servers, Privacy and Data Protection, Local API Servers, Audio Transcriptions, Hardware Acceleration Abstractions.
تشمل البدائل مفتوحة المصدر لـ microsoft/foundry-local: soniqo/speech-swift — This project is a comprehensive toolkit for on-device speech recognition, synthesis, and audio processing,… google-ai-edge/gallery — This project is a development framework for building edge-based AI agents that perform multimodal inference and… cocktailpeanut/dalai — The simplest way to run LLaMA on your local machine. fmhy/fmhy — FMHY is a community-driven index designed to organize and distribute decentralized digital content through… bentoml/bentoml — BentoML is a machine learning model serving framework and GPU-accelerated inference server designed to package,… cactus-compute/cactus — Cactus is an on-device AI inference engine designed for executing large language models, vision models, and…
This project is a comprehensive toolkit for on-device speech recognition, synthesis, and audio processing, specifically engineered for Apple Silicon. It provides a framework for building real-time, full-duplex voice agents that operate entirely offline, leveraging native hardware acceleration to maintain performance and privacy. By utilizing optimized machine learning models, the library enables local execution of complex audio tasks without reliance on external cloud services. The library distinguishes itself through its specialized focus on local, high-performance voice interaction. It incl
This project is a development framework for building edge-based AI agents that perform multimodal inference and system-level automation directly on mobile devices. By prioritizing local-first execution, the platform ensures data privacy and offline functionality, allowing developers to run large language models on hardware without requiring external server connectivity. The framework distinguishes itself through an integrated orchestration layer that connects language models to custom tools, scripts, and native device intents. It provides a structured registry for mapping natural language ins
The simplest way to run LLaMA on your local machine
FMHY is a community-driven index designed to organize and distribute decentralized digital content through standardized metadata and protocol-agnostic linking. It functions as a resilient, distributed map of internet resources, providing a structured directory that facilitates the discovery of media, software, and educational tools without reliance on centralized control. The project distinguishes itself by maintaining a massive, human-verified repository of external links that span diverse digital ecosystems, including peer-to-peer networks, Usenet, and direct download servers. By utilizing