Showing 4 open source projects for "language processing"

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  • 1
    ChatGLM.cpp

    ChatGLM.cpp

    C++ implementation of ChatGLM-6B & ChatGLM2-6B & ChatGLM3 & GLM4(V)

    ChatGLM.cpp is a C++ implementation of the ChatGLM-6B model, enabling efficient local inference without requiring a Python environment. It is optimized for running on consumer hardware.
    Downloads: 9 This Week
    Last Update:
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  • 2
    OpenVINO

    OpenVINO

    OpenVINO™ Toolkit repository

    OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference. Boost deep learning performance in computer vision, automatic speech recognition, natural language processing and other common tasks. Use models trained with popular frameworks like TensorFlow, PyTorch and more. Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. ...
    Downloads: 26 This Week
    Last Update:
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  • 3
    Bolt NLP

    Bolt NLP

    Bolt is a deep learning library with high performance

    Bolt is a high-performance deep learning inference framework developed by Huawei Noah's Ark Lab. It is designed to optimize and accelerate the deployment of deep learning models across various hardware platforms. Bolt is a light-weight library for deep learning. Bolt, as a universal deployment tool for all kinds of neural networks, aims to automate the deployment pipeline and achieve extreme acceleration. Bolt has been widely deployed and used in many departments of HUAWEI company, such as...
    Downloads: 8 This Week
    Last Update:
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  • 4
    TurboTransformers

    TurboTransformers

    Fast and user-friendly runtime for transformer inference

    TurboTransformers is a high-performance inference framework optimized for running Transformer models efficiently on CPUs and GPUs. It improves latency and throughput for NLP applications.
    Downloads: 0 This Week
    Last Update:
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