model_fit objects are created from the `parsnip`

package.

## Usage

```
# S3 method for model_fit
axe_call(x, verbose = FALSE, ...)
# S3 method for model_fit
axe_ctrl(x, verbose = FALSE, ...)
# S3 method for model_fit
axe_data(x, verbose = FALSE, ...)
# S3 method for model_fit
axe_env(x, verbose = FALSE, ...)
# S3 method for model_fit
axe_fitted(x, verbose = FALSE, ...)
```

## Arguments

- x
A model object.

- verbose
Print information each time an axe method is executed. Notes how much memory is released and what functions are disabled. Default is

`FALSE`

.- ...
Any additional arguments related to axing.

## Examples

```
library(parsnip)
library(rpart)
# Create model and fit
lm_fit <- linear_reg() %>%
set_engine("lm") %>%
fit(mpg ~ ., data = mtcars)
out <- butcher(lm_fit, verbose = TRUE)
#> ✔ Memory released: 6.54 kB
# Another parsnip model
rpart_fit <- decision_tree(mode = "regression") %>%
set_engine("rpart") %>%
fit(mpg ~ ., data = mtcars, minsplit = 5, cp = 0.1)
out <- butcher(rpart_fit, verbose = TRUE)
#> ✔ Memory released: 55.18 kB
```