Showing 5 open source projects for "optimization"

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  • 1
    LLMFarm

    LLMFarm

    llama and other large language models on iOS and MacOS offline

    ...LLMFarm is particularly useful for developers and researchers experimenting with local AI systems, as it lowers the barrier to entry for running and testing models without extensive setup. It also supports optimization techniques to improve performance on limited hardware, making it viable for smaller-scale deployments.
    Downloads: 0 This Week
    Last Update:
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  • 2
    AiToEarn

    AiToEarn

    Let's use AI to Earn

    ...The project supports matrix publishing to major global platforms like TikTok, YouTube, Instagram, Facebook, Pinterest, Twitter (X), and several Chinese social networks, enabling a “create once, publish everywhere” workflow. AI automation assists with tasks like title and caption creation, batch content generation, and optimization for each channel’s format and audience. Developers can run or extend AiToEarn locally using Node.js or via its desktop and web apps, and the open-source architecture encourages customization and community contributions.
    Downloads: 11 This Week
    Last Update:
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  • 3
    nndeploy

    nndeploy

    An Easy-to-Use and High-Performance AI Deployment Framework

    ...The system supports multiple inference engines and hardware accelerators, allowing the same AI workflow to run on different platforms without significant modifications. nndeploy also includes performance optimization techniques such as parallel execution, memory reuse, and hardware-accelerated operations to improve inference speed.
    Downloads: 0 This Week
    Last Update:
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  • 4
    MACE

    MACE

    Deep learning inference framework optimized for mobile platforms

    ...Mechanism like automatically breaking OpenCL kernel into small units is introduced to allow better preemption for the UI rendering task. Graph level memory allocation optimization and buffer reuse are supported. The core library tries to keep minimum external dependencies to keep the library footprint small.
    Downloads: 0 This Week
    Last Update:
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  • 5
    TNN

    TNN

    Uniform deep learning inference framework for mobile

    ...It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's mainstream open source frameworks, and expands the support for X86 and NV GPUs. On the mobile phone, TNN has been used by many applications such as mobile QQ, weishi, and Pitu. ...
    Downloads: 0 This Week
    Last Update:
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