Showing 5 open source projects for "work"

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  • 1
    Open Source Vizier

    Open Source Vizier

    Python-based research interface for blackbox

    Open Source (OSS) Vizier is a Python-based interface for blackbox optimization and research, based on Google’s original internal Vizier, one of the first hyperparameter tuning services designed to work at scale. Allows a user to setup an OSS Vizier Server, which can host black-box optimization algorithms to serve multiple clients simultaneously in a fault-tolerant manner to tune their objective functions. Defines abstractions and utilities for implementing new optimization algorithms for research and to be hosted in the service. ...
    Downloads: 7 This Week
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  • 2
    nanoGPT

    nanoGPT

    The simplest, fastest repository for training/finetuning models

    ...While simple, it can still train non-trivial models on modern GPUs and generate coherent text. The project has become widely used in tutorials, courses, and experiments for people learning how transformers work under the hood.
    Downloads: 3 This Week
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  • 3
    moebinv

    moebinv

    C++ libraries for manipulations in non-Euclidean geometry

    ...Both libraries are based on the Clifford algebra capacities of the GiNaC computer algebra system (http://ginac.de). Besides C++ libraries there is a Python wrapper, which can be used in interactive mode (https://codeocean.com/capsule/7952650/). Both libraries work in arbitrary dimensions and signatures of metric. Additionally, there are some 2D/3D-specific routines including a visualisation to PostScript files through Asymptote (http://asymptote.sourcefourge.net) software. The source is written in literate programming NoWeb.
    Downloads: 89 This Week
    Last Update:
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  • 4
    DIG

    DIG

    A library for graph deep learning research

    The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. ...
    Downloads: 0 This Week
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  • 5
    This is a Content Based Image Retrieval Interface with only color features implemented. This is part of a thesis work to analyze the different color features and observe the performance on mainly corel5k images.
    Downloads: 0 This Week
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