This repo contains reference examples for using the MosaicML platform to train and deploy machine learning models at scale. It's designed to be easily forked/copied and modified.
It is structured with four different types of examples:
Please see the README in each folder for more information about each type of example.
To run the lint and test suites for a specific folder, you can use the lint_subdirectory.sh and test_subdirectory.sh scripts:
bash ./scripts/lint_subdirectory.sh benchmarks/bert
bash ./scripts/test_subdirectory.sh benchmarks/bert
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This repo contains reference examples for using the MosaicML platform to train and deploy machine learning models at scale. It's designed to be easily forked/copied and modified.
It is structured with four different types of examples:
Please see the README in each folder for more information about each type of example.
To run the lint and test suites for a specific folder, you can use the lint_subdirectory.sh and test_subdirectory.sh scripts:
bash ./scripts/lint_subdirectory.sh benchmarks/bert
bash ./scripts/test_subdirectory.sh benchmarks/bert
(top 30 of 36)
Shell
100.0%