tfhub: Interface to 'TensorFlow' Hub

'TensorFlow' Hub is a library for the publication, discovery, and consumption of reusable parts of machine learning models. A module is a self-contained piece of a 'TensorFlow' graph, along with its weights and assets, that can be reused across different tasks in a process known as transfer learning. Transfer learning train a model with a smaller dataset, improve generalization, and speed up training.

Version: 0.8.0
Imports: reticulate (≥ 1.9.0.9002), tensorflow (≥ 1.8.0.9006), magrittr, rstudioapi (≥ 0.7)
Suggests: testthat (≥ 2.1.0), knitr, tfestimators, keras, rmarkdown, callr, recipes, tibble, abind, fs, pins, magick
Published: 2020-05-22
Author: Daniel Falbel [aut, cre], JJ Allaire [aut], RStudio [cph, fnd], Google Inc. [cph]
Maintainer: Daniel Falbel <daniel at rstudio.com>
BugReports: https://github.com/rstudio/tfhub/issues
License: Apache License 2.0
URL: https://github.com/rstudio/tfhub
NeedsCompilation: no
SystemRequirements: TensorFlow >= 2.0 (https://www.tensorflow.org/)
Materials: README
CRAN checks: tfhub results

Downloads:

Reference manual: tfhub.pdf
Vignettes: TensorFlow Hub with Keras
Overview
Key concepts
Package source: tfhub_0.8.0.tar.gz
Windows binaries: r-devel: tfhub_0.8.0.zip, r-release: tfhub_0.8.0.zip, r-oldrel: tfhub_0.8.0.zip
macOS binaries: r-release: tfhub_0.7.0.tgz, r-oldrel: tfhub_0.8.0.tgz
Old sources: tfhub archive

Linking:

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