Hi all, I have what I think should be an easy question. I am hoping to teach my students how to save models that were fit using tidymodels to use later. For example, they might use a model in a Shiny app. I think of this as a mini "put the model into production" exercise. Right now, I show them how to do this using saveRDS(), but it seems like that's a bad idea since it sucks a lot of memory. From this tidypredict info, it seems I should be using parse_model() and write_yml() instead? Maybe combined with something from butcher to make the file smaller? Can anyone direct me to an example where this is done? Thanks so much!
This is a little out of date now, but you can check out the very end of this example training script for an example approach.
Some things I would do definitely as of today:
- Use
extract_workflow()
to get the trained workflow out of thelast_fit()
object. - (Optional) Use butcher on the workflow for models that aren't already as streamlined as the one used for the demonstration.
- Probably use
readr::write_rds()
because I like the defaults better.
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Thanks! This should be a great start for what I need for my class.
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