Learn R Programming

⚠️There's a newer version (0.8.1) of this package.Take me there.

tfhub

The tfhub package provides R wrappers to TensorFlow Hub.

TensorFlow Hub is a library for reusable machine learning modules.

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 can:

  • Train a model with a smaller dataset,
  • Improve generalization, and
  • Speed up training.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("rstudio/tfhub")

After installing the tfhub package you need to install the TensorFlow Hub python module:

library(tfhub)
install_tfhub()

Go to the website for more information.

Copy Link

Version

Install

install.packages('tfhub')

Monthly Downloads

286

Version

0.8.0

License

Apache License 2.0

Issues

Pull Requests

Stars

Forks

Maintainer

Daniel Falbel

Last Published

May 22nd, 2020

Functions in tfhub (0.8.0)

hub_load

Hub Load
hub_sparse_text_embedding_column

Module to construct dense representations from sparse text features.
reexports

Objects exported from other packages
hub_image_embedding_column

Module to construct a dense 1-D representation from the pixels of images.
hub_text_embedding_column

Module to construct a dense representation from a text feature.
layer_hub

Hub Layer
bake.step_pretrained_text_embedding

Bake method for step_pretrained_text_embedding
install_tfhub

Install TensorFlow Hub
step_pretrained_text_embedding

Pretrained text-embeddings
%>%

Pipe operator
prep.step_pretrained_text_embedding

Prep method for step_pretrained_text_embedding