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    Build Agents and Models on One Platform

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    Host LLMs in Production With On-Demand GPUs

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  • 1
    tt-metal

    tt-metal

    TT-NN operator library, and TT-Metalium low level kernel programming

    tt-metal, also referred to in its documentation as TT-Metalium, is Tenstorrent’s low-level software development kit for programming applications on Tenstorrent AI accelerators. The project is designed for developers who need direct access to the company’s Tensix processor architecture, exposing a programming model that is closer to hardware control than high-level inference frameworks. Instead of following a traditional GPU model centered on massive thread parallelism, the platform is built...
    Downloads: 26 This Week
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  • 2
    Tiny CUDA Neural Networks

    Tiny CUDA Neural Networks

    Lightning fast C++/CUDA neural network framework

    ...It will likely only work on an RTX 3090, an RTX 2080 Ti, or high-end enterprise GPUs. Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding.
    Downloads: 0 This Week
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  • 3
    Neural Networks Collection

    Neural Networks Collection

    Neural Networks Collection

    This project implements in C++ a bunch of known Neural Networks. So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people.
    Downloads: 1 This Week
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  • 4
    libfastknn

    libfastknn

    Fast C++ KNN classifier

    KNN Classifier library for C++, at background using armadillo. In k-NN classification, the output is a class membership. An object is classified by a majority vote of its neighbors, with the object being assigned to the class most common among its k nearest neighbors (k is a positive integer, typically small). If k = 1, then the object is simply assigned to the class of that single nearest neighbor.
    Downloads: 0 This Week
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    Train ML Models With SQL You Already Know

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    Downloads: 0 This Week
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  • 6
    The name stands for ensemble learning framework. It is a collection of machine learning algorithms for classification and regression with the possibility of connecting them together via ensemble learning. It is written in C++.
    Downloads: 0 This Week
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  • 7
    nn-utility is a neural network library for C++ and Java. Its aim is to simplify the tedious programming of neural networks, while allowing programmers to have maximum flexibility in terms of defining functions and network topology.
    Downloads: 0 This Week
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  • 8
    The aim of the project is to provide a code base to support simulation of physical agents in virtual environments so to experiment with different combinations of NN and evolutive programming paradigms.
    Downloads: 0 This Week
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  • 9
    The goal of the project it to learn how to use Neural Networks, and teach one how to play tic tac toe, and get to the never losing ability that most people can play at.
    Downloads: 0 This Week
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    Patching and Endpoint Management for Under $1/Endpoint

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