Showing 4 open source projects for "open world"

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    Machine Learning Systems

    Machine Learning Systems

    Introduction to Machine Learning Systems

    Machine Learning Systems is an open educational repository that serves as the source and learning stack for the Machine Learning Systems textbook, a project focused on teaching how to engineer AI systems that work reliably in real-world environments. Rather than concentrating only on model training, the material emphasizes the broader discipline of AI engineering, covering efficiency, reliability, deployment, and evaluation across the full lifecycle of intelligent systems. ...
    Downloads: 84 This Week
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  • 2
    KoboldAI

    KoboldAI

    Your gateway to GPT writing

    This is a browser-based front-end for AI-assisted writing with multiple local & remote AI models. It offers the standard array of tools, including Memory, Author's Note, World Info, Save & Load, adjustable AI settings, formatting options, and the ability to import existing AI Dungeon adventures. You can also turn on Adventure mode and play the game like AI Dungeon Unleashed. Stories can be played like a Novel, a text adventure game or used as a chatbot with an easy toggles to change...
    Downloads: 85 This Week
    Last Update:
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  • 3
    Pwnagotchi

    Pwnagotchi

    Deep Reinforcement learning instrumenting bettercap for WiFi pwning

    Pwnagotchi is an A2C-based “AI” powered by bettercap and running on a Raspberry Pi Zero W that learns from its surrounding WiFi environment in order to maximize the crackable WPA key material it captures (either through passive sniffing or by performing deauthentication and association attacks). This material is collected on disk as PCAP files containing any form of handshake supported by hashcat, including full and half WPA handshakes as well as PMKIDs. Instead of merely playing Super Mario...
    Downloads: 4 This Week
    Last Update:
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  • 4
    CrypTen

    CrypTen

    A framework for Privacy Preserving Machine Learning

    CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic...
    Downloads: 0 This Week
    Last Update:
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