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2 repositorios

Awesome GitHub RepositoriesInference Acceleration Drivers

Configuration interfaces for mapping inference workloads to specific hardware-level acceleration libraries.

Explore 2 awesome GitHub repositories matching operating systems & systems programming · Inference Acceleration Drivers. Refine with filters or upvote what's useful.

Awesome Inference Acceleration Drivers GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • paddlepaddle/paddleocrAvatar de PaddlePaddle

    PaddlePaddle/PaddleOCR

    82,412Ver en GitHub↗

    PaddleOCR is a comprehensive optical character recognition framework designed for detecting and transcribing text from images and documents into structured, machine-readable formats. It provides a modular computer vision pipeline that decouples image preprocessing, text detection, and character recognition into independent, configurable stages. This architecture supports automated document digitization and multilingual text recognition, capable of identifying text in over one hundred languages across diverse environments ranging from scanned documents to industrial scenes. The framework disti

    Configures hardware-level acceleration libraries to bridge the gap between high-level recognition software and physical device drivers.

    Pythonai4sciencechineseocrdocument-parsing
    Ver en GitHub↗82,412
  • openvinotoolkit/openvinoAvatar de openvinotoolkit

    openvinotoolkit/openvino

    10,414Ver en GitHub↗

    OpenVINO is an AI inference engine and model serving platform designed to execute optimized deep learning models across CPUs, GPUs, and NPUs through a unified API. It includes a model optimization toolkit for converting, quantizing, and compressing models from various frameworks, alongside a specialized generative AI runtime for large language models. The project distinguishes itself through a plugin-based hardware acceleration layer that maps neural network operations to vendor-specific drivers. It features advanced execution mechanisms such as continuous batching, speculative decoding, and

    Implements a plugin-based system that maps neural network operations to vendor-specific hardware drivers.

    C++aicomputer-visiondeep-learning
    Ver en GitHub↗10,414
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