Showing 3 open source projects for "ml-so1v"

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  • 1
    XNNPACK

    XNNPACK

    High-efficiency floating-point neural network inference operators

    XNNPACK is a highly optimized, low-level neural network inference library developed by Google for accelerating deep learning workloads across a variety of hardware architectures, including ARM, x86, WebAssembly, and RISC-V. Rather than serving as a standalone ML framework, XNNPACK provides high-performance computational primitives—such as convolutions, pooling, activation functions, and arithmetic operations—that are integrated into higher-level frameworks like TensorFlow Lite, PyTorch Mobile, ONNX Runtime, TensorFlow.js, and MediaPipe. The library is written in C/C++ and designed for maximum portability, efficiency, and performance, leveraging platform-specific instruction sets (e.g., NEON, AVX, SIMD) for optimized execution. ...
    Downloads: 3 This Week
    Last Update:
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  • 2
    TensorFlow MacOS

    TensorFlow MacOS

    TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute

    This repository provided a pre-release of TensorFlow and TensorFlow Addons tailored for macOS 11+ with native hardware acceleration via Apple’s ML Compute, supporting both Apple Silicon (M1) and Intel Macs. It shipped ready-made Python 3.8 wheels and install scripts so developers could quickly get an accelerated stack running without building from source. As TensorFlow added a Metal PluggableDevice path, the project directed users toward using Apple’s tensorflow-metal to get GPU acceleration on Mac directly through Metal. ...
    Downloads: 0 This Week
    Last Update:
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  • 3
    This project is a lightweight server written in Ocaml for highly interactive webpages or even online browser based games. The server can already be used as a fast frontend to a MySQL database. The software should work on *nix and windows.
    Downloads: 0 This Week
    Last Update:
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