Retrieve Token Embeddings

Usage

# S3 method for class 'embeddings'
predict(object, newdata, drop = TRUE, .keep_missing = FALSE)

Arguments

object: an embeddings object made by load_embeddings() or as.embeddings()
newdata: a character vector of tokens
drop: logical. If TRUE (the default) and the result is one-dimensional (e.g. a single row), the output will be a (named) vector.
.keep_missing: logical. What should be done about items in newdata that are not present in the embeddings object? If FALSE (the default), they will be ignored. If TRUE, they will be returned as NA.

Details

Duplicated items in newdata will result in duplicated rows in the output. If an item in newdata matches multiple rows in object, the last one will be returned.

Value

Either an embeddings object with a row for each item in newdata, or, when newdata is of length 1, a named numeric vector.

Examples

words <- c("happy", "sad")

texts_embeddings <- predict(glove_twitter_25d, words)
texts_embeddings
#> # 25-dimensional embeddings with 2 rows
#>       dim_1 dim_2 dim_3 dim_4 dim_5 dim_6 dim_7 dim_8 dim_9 dim..      
#> happy -1.23  0.48  0.14 -0.03 -0.65 -0.19  2.10  1.75 -1.30 -0.32 ...  
#> sad    0.04 -0.19  0.44 -0.15 -0.60  0.05  1.47  0.14 -0.72  0.43 ...