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Collective Knowledge (CK) is an educational community project to learn 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 using MLCommons CM (Collective Mind workflow automation framework)
A collection of portable workflows, automation recipes and components for MLOps in a unified CK format. Note that this repository is outdated - please check the 2nd generation of the CK workflow automation meta-framework with portable MLOps and DevOps components here:
This repository shows an example of how to use the ONNX standard to interoperate between different frameworks. In this example, we train a model with PyTorch and make predictions with Tensorflow, ONNX Runtime, and Caffe2.
CM interface and automation recipes to make it easier to run and reproduce experiments from research projects across diverse and continuously changing models, data sets, software and hardware