hub_text_embedding_column: Module to construct a dense representation from a text...
In tfhub: Interface to 'TensorFlow' Hub
Description
This feature column can be used on an input feature whose values are strings of
arbitrary size.
Usage
1
hub_text_embedding_column(key, module_spec, trainable = FALSE)
Arguments
key
A string or [feature_column](https://tensorflow.rstudio.com/tfestimators/articles/feature_columns.html)
identifying the text feature.
module_spec
A string handle or a _ModuleSpec identifying the module.
trainable
Whether or not the Module is trainable. 'FALSE' by default,
meaning the pre-trained weights are frozen. This is different from the ordinary
'tf.feature_column.embedding_column()', but that one is intended for training
from scratch.
tfhub documentation built on Dec. 19, 2021, 9:07 a.m.
R Package Documentation
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Description
This feature column can be used on an input feature whose values are strings of arbitrary size.
Usage
1 | hub_text_embedding_column(key, module_spec, trainable = FALSE)
|
Arguments
key |
A string or [feature_column](https://tensorflow.rstudio.com/tfestimators/articles/feature_columns.html) identifying the text feature. |
module_spec |
A string handle or a _ModuleSpec identifying the module. |
trainable |
Whether or not the Module is trainable. 'FALSE' by default, meaning the pre-trained weights are frozen. This is different from the ordinary 'tf.feature_column.embedding_column()', but that one is intended for training from scratch. |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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