Showing 4 open source projects for "network security toolkit"

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    ProjectLibre - Project Management

    ProjectLibre - Project Management

    #1 alternative to Microsoft Project : Project Management & Gantt Chart

    .... 🌐 Try the Cloud: http://www.projectlibre.com/register/trial πŸ’» Mac tip: If blocked, go to System Preferences β†’ Security β†’ Allow install πŸ† InfoWorld β€œBest of Open Source” β€’ Used at 1,700+ universities β€’ 250K+ community πŸ™ Support us: http://www.gofundme.com/f/projectlibre-free-open-source-development
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    Downloads: 16,085 This Week
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  • 2
    Kaleidoscope-SDK

    Kaleidoscope-SDK

    User toolkit for analyzing and interfacing with Large Language Models

    kaleidoscope-sdk is a Python module used to interact with large language models hosted via the Kaleidoscope service available at: https://github.com/VectorInstitute/kaleidoscope. It provides a simple interface to launch LLMs on an HPC cluster, asking them to perform basic features like text generation, but also retrieve intermediate information from inside the model, such as log probabilities and activations. Users must authenticate using their Vector Institute cluster credentials. This can...
    Downloads: 0 This Week
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  • 3
    DomE

    DomE

    Implements a reference architecture for creating information systems

    DomE Experiment is an implementation of a reference architecture for creating information systems from the automated evolution of the domain model. The architecture comprises elements that guarantee user access through automatically generated interfaces for various devices, integration with external information sources, data and operations security, automatic generation of analytical information, and automatic control of business processes. All these features are generated from the domain...
    Downloads: 0 This Week
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  • 4
    CRSLab

    CRSLab

    CRSLab is an open-source toolkit

    CRSLab is an open-source toolkit for building Conversational Recommender System (CRS). It is developed based on Python and PyTorch. CRSLab has the following highlights. Comprehensive benchmark models and datasets: We have integrated commonly-used 6 datasets and 18 models, including graph neural network and pre-training models such as R-GCN, BERT and GPT-2. We have preprocessed these datasets to support these models, and release for downloading.
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