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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.

Version: 0.1.2
Depends: R (≥ 3.6)
Imports: glue, purrr, rlang, utils, withr
Suggests: bonsai, butcher, callr, caret, covr, dbarts, embed, h2o, keras, kernlab, knitr, luz, MASS, modeldata, parsnip, recipes, renv, rmarkdown, stacks, tensorflow, testthat (≥ 3.0.0), torch, torchvision, uwot, vetiver, workflows, xgboost (≥ 1.6.0.1)
Published: 2024-11-12
DOI: 10.32614/CRAN.package.bundle
Author: Julia Silge ORCID iD [aut, cre], Simon Couch [aut], Qiushi Yan [aut], Max Kuhn [aut], Posit Software, PBC [cph, fnd]
Maintainer: Julia Silge <julia.silge at posit.co>
BugReports: https://github.com/rstudio/bundle/issues
License: MIT + file LICENSE
URL: https://github.com/rstudio/bundle, https://rstudio.github.io/bundle/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: bundle results

Documentation:

Reference manual: bundle.pdf
Vignettes: Getting started with bundle (source, R code)

Downloads:

Package source: bundle_0.1.2.tar.gz
Windows binaries: r-devel: bundle_0.1.2.zip, r-release: bundle_0.1.2.zip, r-oldrel: bundle_0.1.2.zip
macOS binaries: r-release (arm64): bundle_0.1.2.tgz, r-oldrel (arm64): bundle_0.1.2.tgz, r-release (x86_64): bundle_0.1.2.tgz, r-oldrel (x86_64): bundle_0.1.2.tgz
Old sources: bundle archive

Reverse dependencies:

Reverse imports: vetiver

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bundle to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.