Showing 4 open source projects for "trains"

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    Build Agents and Models on One Platform

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    Paessler: Easy to Use With Enterprise Power. Free Trial

    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

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    DeepSpec

    DeepSpec

    A full-stack codebase for training and evaluating speculative decoding

    ...It provides the components needed to prepare data, train draft models, and measure acceptance behavior against target models. The workflow starts with data preparation, including prompt download, target answer regeneration, and target cache construction. It then trains a draft model using configuration files for different algorithms and target model setups. The evaluation pipeline measures speculative decoding performance across benchmark tasks such as math, coding, instruction-following, and chat-style datasets. Overall, it is useful for researchers and engineers studying faster language model inference through speculative decoding methods.
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  • 2
    Detectron2

    Detectron2

    Next-generation platform for object detection and segmentation

    ...Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll open source more research projects in this way. It trains much faster. Models can be exported to TorchScript format or Caffe2 format for deployment. With a new, more modular design, Detectron2 is flexible and extensible, and able to provide fast training on single or multiple GPU servers. Detectron2 includes high-quality implementations of state-of-the-art object detection.
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  • 3
    BudgetedSVM

    BudgetedSVM

    BudgetedSVM: A C++ Toolbox for Large-scale, Non-linear Classification

    We present BudgetedSVM, a C++ toolbox containing highly optimized implementations of three recently proposed algorithms for scalable training of Support Vector Machine (SVM) approximators: Adaptive Multi-hyperplane Machines (AMM), Budgeted Stochastic Gradient Descent (BSGD), and Low-rank Linearization SVM (LLSVM). BudgetedSVM trains models with accuracy comparable to LibSVM in time comparable to LibLinear, as it allows solving highly non-linear classi fication problems with millions of high-dimensional examples within minutes on a regular personal computer. We provide command-line and Matlab interfaces to BudgetedSVM, efficient API for handling large-scale, high-dimensional data sets, as well as detailed documentation to help developers use and further extend the toolbox.
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  • 4
    BayesianCortex

    BayesianCortex

    simple algorithm for a realtime interactive visual cortex for painting

    A paint program where the canvas is the visual cortex of a simple kind of artificial intelligence. You paint with the mouse into its dreams and it responds by changing what you painted gradually. There will also be an API for using it with other programs as a general high-dimensional space. Each pixel's brightness is its own dimension. Bayesian nodes have exactly 3 childs because that is all thats needed to do NAND in a fuzzy way as Bayes' Rule which is NAND at certain extremes. NAND can be...
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    Endpoint Management with Remote Control Built In

    Patch, monitor, and connect to Windows and macOS devices from one console

    Splashtop AEM handles patching, alerts, scripts, and inventory, and unattended remote control is included. When something needs hands-on work, you’re one click away instead of switching tools.
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