How do I use the pipe operator or something related to break a pipeline into two steps?

Question

Is there a way to break this into two steps so that the ml_logistic_regression() can be applied separately to flights_pipeline?

Below is working code for the pipeline:

flights_pipeline <- ml_pipeline(sc) %>%
  ft_dplyr_transformer(
    tbl = df
    ) %>%
  ft_binarizer(
    input_col = "dep_delay",
    output_col = "delayed",
    threshold = 15
  ) %>%
  ft_bucketizer(
    input_col = "sched_dep_time",
    output_col = "hours",
    splits = c(400, 800, 1200, 1600, 2000, 2400)
  )  %>%
  ft_r_formula(delayed ~ month + day + hours + distance) %>% 
  ml_logistic_regression()

This is my attempt, I'd like to break it into two steps - something like this:

flights_pipeline <- ml_pipeline(sc) %>%
  ft_dplyr_transformer(
    tbl = df
    ) %>%
  ft_binarizer(
    input_col = "dep_delay",
    output_col = "delayed",
    threshold = 15
  ) %>%
  ft_bucketizer(
    input_col = "sched_dep_time",
    output_col = "hours",
    splits = c(400, 800, 1200, 1600, 2000, 2400)
  )  %>%
  ft_r_formula(delayed ~ month + day + hours + distance)

flights_pipeline_with_model <- flights_pipeline %>% 
  ml_logistic_regression()