Showing 3 open source projects for "performance"

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    Google AI Edge Gallery

    Google AI Edge Gallery

    A gallery that showcases on-device ML/GenAI use cases

    ...The project bundles runnable samples that show how to run TensorFlow Lite/Edge TPU models (and similar lightweight runtimes) on mobile and embedded platforms, demonstrating common tasks like image classification, object detection, audio recognition, and pose estimation. Each sample is intended to be both a learning aid and a practical starting point: code is organized to show model loading, pre/post-processing, performance measurement, and common optimization knobs (quantization, NNAPI/Delegate usage, and hardware accelerators). The repo also collects small, well-documented models and conversion scripts so developers can reproduce a pipeline from a full-size model down to a device-friendly artifact.
    Downloads: 183 This Week
    Last Update:
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  • 2
    askimo

    askimo

    AI desktop app with local RAG, privacy-first, multi-model support

    ...Askimo is built around project-based sessions, customizable conversation styles (directives), and searchable local history, making it well suited for document analysis, research, planning, and daily business workflows. The application runs on macOS, Windows, and Linux, with a strong focus on usability, performance, and transparency.
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    Downloads: 27 This Week
    Last Update:
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  • 3
    AppShark

    AppShark

    Static taint analysis platform to scan vulnerabilities

    AppShark is an open-source static taint-analysis platform developed by ByteDance designed to scan Android application packages (APKs) for potential security or privacy vulnerabilities. It performs code analysis without executing the app — inspecting APK contents, tracking data flows (taints), and detecting risky patterns such as insecure file access, unsafe API usage, resource-leak possibilities, or misconfigurations. Users can customize scanning via rule sets (written in JSON), defining...
    Downloads: 0 This Week
    Last Update:
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