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On-Device Inference Engines · Awesome GitHub Repositories

2 repos

Awesome GitHub RepositoriesOn-Device Inference Engines

Runtimes optimized for executing machine learning models locally on edge hardware to minimize latency and bandwidth usage.

Distinguishing note: Distinct from general ML frameworks: specifically optimized for local, low-latency execution on edge devices.

Explore 2 awesome GitHub repositories matching artificial intelligence & ml · On-Device Inference Engines. Refine with filters or upvote what's useful.

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  • google-ai-edge/mediapipe

    google-ai-edge/mediapipe

    33,820View on GitHub↗

    MediaPipe is a cross-platform machine learning framework designed for deploying vision, audio, and text processing models across mobile, desktop, and web environments. It functions as an on-device inference engine that executes complex models locally on edge hardware, ensuring low latency and privacy without requiring a constant internet connection. The framework utilizes a graph-based pipeline orchestration system where data flows through a directed network of modular calculators to ensure synchronized and deterministic processing. It distinguishes itself through a unified runtime that provi

    A high-performance runtime that executes complex machine learning models locally on edge hardware to ensure low latency and privacy.

    C++androidaudio-processingc-plus-plus
    33,820View on GitHub↗
  • ente-io/ente

    ente-io/ente

    24,592View on GitHub↗

    Ente is a privacy-focused platform for end-to-end encrypted storage and two-factor authentication management. It functions as a zero-knowledge identity provider, ensuring that all cryptographic operations, key derivation, and data encryption occur locally on the user's device. By maintaining this architecture, the service provider remains unable to access or decrypt any stored personal information or authentication credentials. The platform distinguishes itself through a combination of on-device intelligence and resilient data distribution. It utilizes a local machine learning engine to perfo

    Perform machine learning tasks like semantic search and face recognition locally on the user device to ensure that sensitive data remains private and fully encrypted.

    Dart2faandroidauthy
    24,592View on GitHub↗