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@mlcommons

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 487

  3. mlcube mlcube Public

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

    Python 151 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 13 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.

    7 5

Repositories

Showing 10 of 80 repositories
  • cm4mlops Public

    A collection of reusable and cross-platform automation recipes (CM scripts) with a human-friendly interface and minimal dependencies to make it easier to build, run, benchmark and optimize AI, ML and other applications and systems across diverse and continuously changing models, data sets, software and hardware (cloud/edge)

    Python 4 Apache-2.0 2 3 0 Updated Apr 27, 2024
  • dynabench Public
    Python 13 MIT 14 7 (1 issue needs help) 3 Updated Apr 27, 2024
  • modelbench Public

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

    Python 27 Apache-2.0 2 58 4 Updated Apr 27, 2024
  • medperf Public

    An open benchmarking platform for medical artificial intelligence using Federated Evaluation.

    Python 131 Apache-2.0 26 48 (1 issue needs help) 14 Updated Apr 27, 2024
  • ck Public

    Collective Mind (CM) is a small, modular, cross-platform and decentralized workflow automation framework with a human-friendly interface and reusable automation recipes to make it easier to compose, run, benchmark and optimize AI, ML and other applications and systems across diverse and continuously changing models, data, software and hardware

    Python 580 Apache-2.0 106 62 (4 issues need help) 0 Updated Apr 27, 2024
  • GaNDLF Public

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

    Python 138 Apache-2.0 72 18 (1 issue needs help) 3 Updated Apr 26, 2024
  • modelgauge Public

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

    Python 18 Apache-2.0 2 38 0 Updated Apr 26, 2024
  • chakra Public

    Repository for MLCommons Chakra schema and tools

    Python 27 Apache-2.0 12 3 7 Updated Apr 26, 2024
  • training Public

    Reference implementations of MLPerf™ training benchmarks

    Python 1,554 Apache-2.0 540 48 38 Updated Apr 26, 2024
  • policies Public

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

    Python 24 Apache-2.0 52 34 38 Updated Apr 25, 2024
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