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@mlcommons

MLCommons

Better ML for everyone
README.md

MLCommons

The mission of MLCommons™ is to make machine learning better for everyone. Together with its 50+ founding Members and Affiliates, including startups, leading companies, academics, and non-profits from around the globe, MLCommons will help grow machine learning from a research field into a mature industry through benchmarks, public datasets and best practices. MLCommons firmly believes in the power of open-source and open data. Our software projects are generally available under the Apache 2.0 license and our datasets generally use CC-BY 4.0.

You can visit the MLCommons website here for more information, or head straight to our Community page if you want to join our Working Groups.

Individuals, companies, and other entities can become members and/or affiliates.

Policies, License and Code of Conduct

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  1. training training Public

    Reference implementations of MLPerf™ training benchmarks

    Python 1.6k 548

  2. inference inference Public

    Reference implementations of MLPerf™ inference benchmarks

    Python 1.1k 506

  3. training_results_v4.0 training_results_v4.0 Public

    This repository contains the results and code for the MLPerf™ Training v4.0 benchmark.

    Python 7 3

  4. inference_results_v4.0 inference_results_v4.0 Public

    This repository contains the results and code for the MLPerf™ Inference v4.0 benchmark.

    9 15

  5. modelbench modelbench Public

    Run safety benchmarks against AI models and view detailed reports showing how well they performed.

    Python 45 7

  6. policies policies Public

    General policies for MLPerf™ including submission rules, coding standards, etc.

    Python 25 54

Repositories

Showing 10 of 85 repositories
  • GaNDLF Public

    A generalizable application framework for segmentation, regression, and classification using PyTorch

    mlcommons/GaNDLF’s past year of commit activity
    Python 150 Apache-2.0 78 19 (1 issue needs help) 8 Updated Jul 19, 2024
  • modelbench Public

    Run safety benchmarks against AI models and view detailed reports showing how well they performed.

    mlcommons/modelbench’s past year of commit activity
    Python 45 Apache-2.0 7 69 3 Updated Jul 19, 2024
  • croissant Public

    Croissant is a high-level format for machine learning datasets that brings together four rich layers.

    mlcommons/croissant’s past year of commit activity
    Python 355 Apache-2.0 38 101 (4 issues need help) 17 Updated Jul 19, 2024
  • inference Public

    Reference implementations of MLPerf™ inference benchmarks

    mlcommons/inference’s past year of commit activity
    Python 1,148 Apache-2.0 506 124 20 Updated Jul 19, 2024
  • mobile_app_open Public

    Mobile App Open

    mlcommons/mobile_app_open’s past year of commit activity
    C++ 41 Apache-2.0 20 28 3 Updated Jul 19, 2024
  • modelgauge Public

    Make it easy to automatically and uniformly measure the behavior of many AI Systems.

    mlcommons/modelgauge’s past year of commit activity
    Python 23 Apache-2.0 5 63 3 Updated Jul 19, 2024
  • policies Public

    General policies for MLPerf™ including submission rules, coding standards, etc.

    mlcommons/policies’s past year of commit activity
    Python 25 Apache-2.0 54 35 41 Updated Jul 18, 2024
  • logging Public

    MLPerf™ logging library

    mlcommons/logging’s past year of commit activity
    Python 29 Apache-2.0 46 40 2 Updated Jul 18, 2024
  • dynabench Public
    mlcommons/dynabench’s past year of commit activity
    Python 16 MIT 15 7 (1 issue needs help) 5 Updated Jul 18, 2024
  • algorithmic-efficiency Public

    MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvements in both training algorithms and models.

    mlcommons/algorithmic-efficiency’s past year of commit activity
    Python 316 Apache-2.0 60 23 5 Updated Jul 18, 2024
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