• AI-generated apps that pass security review Icon
    AI-generated apps that pass security review

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    Retool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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    Outgrown Windows Task Scheduler?

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  • 1
    ncnn

    ncnn

    High-performance neural network inference framework for mobile

    ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including...
    Downloads: 33 This Week
    Last Update:
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  • 2
    shuyuan

    shuyuan

    Reading book source

    ...The name suggests “academy” or “study hall,” and the tool aims to help users ingest, organize, and manage reading content — possibly offering features like text parsing, annotation, metadata generation, translation, or storage for later reference. The repository is set up to support document ingestion, indexing, and maybe some AI-aided summarization or lookup functions, which helps users convert large text corpora into a structured, searchable knowledge base. For learners, researchers, or avid readers, Shuyuan offers a way to bridge from plain text files or eBooks into a manageable, interactive resource — one where notes, references, and reading progress can be tracked. ...
    Downloads: 0 This Week
    Last Update:
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  • 3
    Apple Neural Engine (ANE) Transformers

    Apple Neural Engine (ANE) Transformers

    Reference implementation of the Transformer architecture optimized

    ANE Transformers is a reference PyTorch implementation of Transformer components optimized for Apple Neural Engine on devices with A14 or newer and on Macs with M1 or newer chips. It demonstrates how to structure attention and related layers to achieve substantial speedups and lower peak memory compared to baseline implementations when deployed to ANE. The repository targets practitioners who want to keep familiar PyTorch modeling while preparing models for Core ML/ANE execution paths. ...
    Downloads: 0 This Week
    Last Update:
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