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# CITATION.cff file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "tabby" in publications use:'
type: software
license: MIT
title: 'tabby: Tidy Interfaces for Tabular Deep Learning'
version: 0.0.1
abstract: Model definitions for fitting, tuning, and predicting with deep learning
  models for tabular data using the 'parsnip' and 'tidymodels' frameworks. Supported
  models include the 'TabPFN' foundation model of Hollmann et al. (2025) <https://doi.org/10.1038/s41586-024-08328-6>,
  'TabICL' by Qu et al. (2025) <https://doi.org/10.48550/arXiv.2502.05564>, 'SAINT'
  by Somepalli et al. (2021) <https://doi.org/10.48550/arXiv.2106.01342>, and the
  tabular 'ResNet' of Gorishniy et al. (2021) <https://doi.org/10.48550/arXiv.2106.11959>,
  among others. Helper functions are also included to create space-filling grids for
  tuning parameters that are defined on a per-layer basis. These functions define
  the model interfaces; the computations are carried out by separate engine packages.
authors:
- family-names: Kuhn
  given-names: Max
  email: max@posit.co
  orcid: https://orcid.org/0000-0003-2402-136X
- family-names: Ruiz
  given-names: Edgar
  email: edgar@posit.co
repository: https://cran.r-universe.dev
repository-code: https://github.com/tidymodels/tabby
commit: 6985e3b8bcc18895117177d7bf6372d9293a8280
url: https://tabby.tidymodels.org/
date-released: '2026-10-15'
contact:
- family-names: Kuhn
  given-names: Max
  email: max@posit.co
  orcid: https://orcid.org/0000-0003-2402-136X