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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
doi: 10.32614/CRAN.package.tabby
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 built on
  'torch'.
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://tidymodels.r-universe.dev
repository-code: https://github.com/tidymodels/tabby
commit: ad4f632c1a2f62d70a554dd2a75f4f47a8093127
url: https://tabby.tidymodels.org/
date-released: '2026-10-01'
contact:
- family-names: Kuhn
  given-names: Max
  email: max@posit.co
  orcid: https://orcid.org/0000-0003-2402-136X