This repository collects together an archive of pre-built machine learning models that can be readily shared for individuals to download and to demonstrate the model in action.
The sample R pre-built models rain-tomorrow, iris-r, and clothes-recommender serve as templates which model package authors can mimic.
One of gpl3 (strong license requiring derivative works to also be open source) or mit (moderate license not limiting derivative work). A LICENSE file is provided within the package.
This can be python or R. The language is then a dependency that is checked for and installed as required.
A list of other packages (and optionally versions) that the model depends on. For python these might form the contents of requirements.txt for a pip install, for example. On Ubuntu, specific OS packages are searched for to be installed before using pip install. Similarly for R packages, OS distributed versions of the packages are sought first and then R's own package installer is used if no OS version found.
Examples:
dependencies: rpart, magrittr
For Ubuntu this might be translated to:
wajig install r-cran-rpart r-cran-magrittr
For Windows this might be translated to:
Rscript -e 'install.packages(c("rpart", "magrittr"))'
The latter is also what would have been run if for Ubuntu no OS packages were found for the dependencies.
The name and email address of the original model developer. This can be different to the person who packages the model for the MLHub.
The name and email address of the person who packaged the model for sharing on ML Hub.
The name and email address of the person who is maintaining the model package for the ML Hub.
Each model archive must come with a license with a LICENSE file capturing the license. Depending on the license of the original model, the model package author may be limited as to the choice of license. Generally favoured licenses include GPL3 and MIT.