Showing 4 open source projects for "android kernel"

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  • 1
    Android Use

    Android Use

    Automate native Android apps with AI using accessibility APIs

    android-action-kernel is an open source Python library designed to let AI agents control and automate native Android applications running on real devices or emulators. It fills a gap in automation tooling by focusing on mobile-first workflows where traditional browser or desktop-based automation doesn’t work; such as logistics, gig work, field operations, and other industries reliant on phones or tablets.
    Downloads: 2 This Week
    Last Update:
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  • 2
    RWKV Runner

    RWKV Runner

    A RWKV management and startup tool, full automation, only 8MB

    RWKV (pronounced as RwaKuv) is an RNN with GPT-level LLM performance, which can also be directly trained like a GPT transformer (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, fast training, saves VRAM, "infinite" ctxlen, and free text embedding. Moreover it's 100% attention-free. Default configs has enabled custom CUDA kernel acceleration, which is much faster and consumes much less VRAM. If you encounter possible compatibility...
    Downloads: 7 This Week
    Last Update:
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  • 3
    Cactus

    Cactus

    Low-latency AI inference engine optimized for mobile devices

    Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing...
    Downloads: 7 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: 1 This Week
    Last Update:
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