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MLCommons

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 Get Involved 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

Pinned

  1. training training Public

    Reference implementations of MLPerf™ training benchmarks

    Python 1.6k 540

  2. inference inference Public

    Reference implementations of MLPerf™ inference benchmarks

    Python 1.1k 493

  3. mlcube mlcube Public

    MLCube® is a project that reduces friction for machine learning by ensuring that models are easily portable and reproducible.

    Python 152 32

  4. policies policies Public

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

    Python 24 52

  5. training_results_v3.1 training_results_v3.1 Public

    This repository contains the results and code for the MLPerf™ Training v3.1 benchmark.

    Python 15 6

  6. inference_results_v4.0 inference_results_v4.0 Public

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

    8 7

Repositories

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