{"repo":"mlcommons/ck","free":true,"listed":false,"github":"https://github.com/mlcommons/ck","clone":"git clone https://github.com/mlcommons/ck.git","description":"Collective Knowledge (CK), Collective Mind (CM/CMX) and MLPerf automations: community-driven projects to learn how to run AI, ML, and other emerging workloads more efficiently and cost-effectively across diverse models, datasets, software, and hardware using MLPerf methodology and benchmarks.","language":"Python","stars":650,"topics":["automation","portability","reusability","collaboration","modularity","mlops","best-practices","education","mlperf","optimization"],"license":"Apache-2.0","category":"workflow-automation","readme_excerpt":"### The next generation of this technology: cMeta CK / CM / CMX are legacy and maintained by MLCommons. Their successor, cMeta , is being developed by the original author here. This legacy project is maintained by MLCommons. The next generation of this technology, cMeta, designed to support collaborative and reproducible AI systems R&D, is being developed by the original author. Collective Knowledge project (CK) Collective Knowledge (CK) is a community-driven project dedicated to supporting open science, enhancing reproducible research, and fostering collaborative learning on how to run AI, ML, and other emerging workloads in the most efficient and cost-effective way across diverse models, data sets, software and hardware: [white paper ]. It includes the following sub-projects. Collective Mind project (MLCommons CM) The Collective Mind automation framework (CM) was developed to support open science and facilitate collaborative, reproducible, and reusable research, development, and experimentation based on FAIR principles. It helps users non-intrusively convert their software projects into file-based repositories of portable and reusable artifacts (code, data, models, scripts) with extensible metadata and reusable automations, a unified command-line interface, and a simple Python API. Such artifacts can be easily chained together into portable and technology-agnostic automation workflows, enabling users to rerun, reproduce, and reuse complex experimental setups across diverse ","default_branch":null,"files":null,"tree":[],"storefront":"/r/mlcommons","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/mlcommons/ck/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}