library(tfhub)
library(tibble)
library(recipes)
<- tibble(text = c('hi', "heello", "goodbye"), y = 0)
df
<- recipe(y ~ text, df)
rec <- rec %>% step_pretrained_text_embedding(
rec
text, handle = "https://tfhub.dev/google/tf2-preview/gnews-swivel-20dim-with-oov/1"
)
step_pretrained_text_embedding
Pretrained text-embeddings
Description
step_pretrained_text_embedding
creates a specification of a recipe step that will transform text data into its numerical transformation based on a pretrained model.
Usage
step_pretrained_text_embedding(
recipe,
..., role = "predictor",
trained = FALSE,
handle, args = NULL,
skip = FALSE,
id = recipes::rand_id("pretrained_text_embedding")
)
Arguments
Arguments | Description |
---|---|
recipe | A recipe object. The step will be added to the sequence of operations for this recipe. |
… | One or more selector functions to choose variables. |
role | Role for the created variables |
trained | A logical to indicate if the quantities for preprocessing have been estimated. |
handle | the Module handle to resolve. |
args | other arguments passed to [hub_load()]. |
skip | A logical. Should the step be skipped when the recipe is baked by [recipes::bake.recipe()]? While all operations are baked when [recipes::prep.recipe()] is run, some operations may not be able to be conducted on new data (e.g. processing the outcome variable(s)). Care should be taken when using skip = TRUE as it may affect the computations for subsequent operations |
id | A character string that is unique to this step to identify it. |