probably.md
In vetiver: Version, Share, Deploy, and Monitor Models

can print int_conformal_split model

Code
  v_split
Output

  -- cars_int_split - <butchered_int_conformal_split> model for deployment 
  A Split Conformal inference with a ranger regression model using 10 features

create plumber.R for int_conformal_split

Code
  cat(readr::read_lines(tmp), sep = "\n")
Output
  # Generated by the vetiver package; edit with care

  library(pins)
  library(plumber)
  library(rapidoc)
  library(vetiver)

  # Packages needed to generate model predictions
  if (FALSE) {
      library(parsnip)
      library(probably)
      library(ranger)
      library(workflows)
  }
  b <- board_folder(path = "<redacted>")
  v <- vetiver_pin_read(b, "cars_int_split")

  #* @plumber
  function(pr) {
      pr |> vetiver_api(v)
  }

can print int_conformal_full model

Code
  v_full
Output

  -- cars_int_full - <butchered_int_conformal_full> model for deployment 
  A full Conformal inference with a ranger regression model using 10 features

create plumber.R for int_conformal_full

Code
  cat(readr::read_lines(tmp), sep = "\n")
Output
  # Generated by the vetiver package; edit with care

  library(pins)
  library(plumber)
  library(rapidoc)
  library(vetiver)

  # Packages needed to generate model predictions
  if (FALSE) {
      library(parsnip)
      library(probably)
      library(ranger)
      library(workflows)
  }
  b <- board_folder(path = "<redacted>")
  v <- vetiver_pin_read(b, "cars_int_full")

  #* @plumber
  function(pr) {
      pr |> vetiver_api(v)
  }

can print int_conformal_quantile model

Code
  v_quantile
Output

  -- cars_int_quantile - <butchered_int_conformal_quantile> model for deployment 
  A quantile Conformal inference with a ranger regression model using 10 features

create plumber.R for int_conformal_quantile

Code
  cat(readr::read_lines(tmp), sep = "\n")
Output
  # Generated by the vetiver package; edit with care

  library(pins)
  library(plumber)
  library(rapidoc)
  library(vetiver)

  # Packages needed to generate model predictions
  if (FALSE) {
      library(parsnip)
      library(probably)
      library(ranger)
      library(workflows)
  }
  b <- board_folder(path = "<redacted>")
  v <- vetiver_pin_read(b, "cars_int_quantile")

  #* @plumber
  function(pr) {
      pr |> vetiver_api(v)
  }

can print int_conformal_cv model

Code
  v_cv
Output

  -- cars_int_cv - <butchered_int_conformal_cv> model for deployment 
  A 10-fold CV+ Conformal inference with a ranger regression model using 10
  features

create plumber.R for int_conformal_cv

Code
  cat(readr::read_lines(tmp), sep = "\n")
Output
  # Generated by the vetiver package; edit with care

  library(pins)
  library(plumber)
  library(rapidoc)
  library(vetiver)

  # Packages needed to generate model predictions
  if (FALSE) {
      library(parsnip)
      library(probably)
      library(ranger)
      library(workflows)
  }
  b <- board_folder(path = "<redacted>")
  v <- vetiver_pin_read(b, "cars_int_cv")

  #* @plumber
  function(pr) {
      pr |> vetiver_api(v)
  }