Package: bundle

Julia Silge

bundle: Serialize Model Objects with a Consistent Interface

Typically, models in 'R' exist in memory and can be saved via regular 'R' serialization. However, some models store information in locations that cannot be saved using 'R' serialization alone. The goal of 'bundle' is to provide a common interface to capture this information, situate it within a portable object, and restore it for use in new settings.

Authors:Julia Silge [aut, cre], Simon Couch [aut], Qiushi Yan [aut], Max Kuhn [aut], Posit Software, PBC [cph, fnd]

bundle.pdf |bundle.html
bundle/json (API)

# Install bundle in R:
install.packages('bundle', repos = c('', ''))

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5 exports 24 stars 2.80 score 8 dependencies 3 dependents 858 downloads

Last updated 21 days agofrom:31f4502132688899c1c897bf18e212757dd414cf



Getting started with bundle

Rendered frombundle.Rmdusingknitr::rmarkdownon May 31 2024.

Last update: 2023-03-07
Started: 2022-07-07

Readme and manuals

Help Manual

Help pageTopics
Bundlingbundle unbundle
bundle: Serialize Model Objects With A Consistent Interfacebundle-package bundle_description
Bundle an 'h2o' objectbundle.H2OAutoML bundle.H2OBinomialModel bundle.H2OMultinomialModel bundle.H2ORegressionModel
Bundle a 'keras'
Bundle a 'luz_module_fitted' objectbundle.luz_module_fitted
Bundle a parsnip 'model_fit' objectbundle.model_fit bundle_model_fit
Bundle a tidymodels 'model_stack' objectbundle.model_stack bundle_model_stack
Bundle a 'recipe' objectbundle.recipe bundle_recipe
Bundle a 'step_umap' objectbundle.step_umap bundle_step_umap
Bundle a caret 'train' objectbundle.train bundle_train
Bundle a tidymodels 'workflow' objectbundle.workflow bundle_workflow
Bundle an 'xgb.Booster' objectbundle.xgb.Booster