README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# tidybert

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[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![R-CMD-check](https://github.com/macmillancontentscience/tidybert/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/macmillancontentscience/tidybert/actions/workflows/R-CMD-check.yaml)
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tidybert implements BERT NLP models with a consistent interface for fitting and creating predictions.
The models are fully compatible with the tidymodels framework.

## Installation

You can install the development version of tidybert from [GitHub](https://github.com/) with:

``` r
# install.packages("remotes")
remotes::install_github("macmillancontentscience/tidybert")
```

## Code of Conduct

Please note that the tidybert project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.

## Disclaimer

This is not an officially supported Macmillan Learning product.

## Contact information

Questions or comments should be directed to Jon Harmon (jonthegeek@gmail.com) and Jonathan Bratt (jonathan.bratt@macmillan.com).