{ "_id": "6ad21bce3c1b78c68c07b0e4", "Package": "tabby", "Title": "Tidy Interfaces for Tabular Deep Learning", "Version": "0.0.1", "Authors@R": "c(\nperson(\"Max\", \"Kuhn\", , \"max@posit.co\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2402-136X\")),\nperson(\"Edgar\", \"Ruiz\", , \"edgar@posit.co\", role = \"aut\"),\nperson(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"),\ncomment = c(ROR = \"03wc8by49\"))\n)", "Description": "Model definitions for fitting, tuning, and predicting with\ndeep learning models for tabular data using the 'parsnip' and\n'tidymodels' frameworks. Supported models include the TabPFN\nfoundation model of Hollmann et al. (2025)\n, TabICL by Qu et al. (2025)\n, SAINT by Somepalli et al.\n(2021) , and the tabular ResNet\nof Gorishniy et al. (2021) ,\namong others. Helper functions are also included to create\nspace-filling grids for tuning parameters that are defined on a\nper-layer basis. These functions define the model interfaces;\nthe computations are carried out by separate engine packages\nbuilt on 'torch'.", "License": "MIT + file LICENSE", "URL": "https://github.com/tidymodels/tabby, https://tabby.tidymodels.org/", "BugReports": "https://github.com/tidymodels/tabby/issues", "Remotes": [ "tidymodels/parsnip" ], "Encoding": "UTF-8", "Language": "en-US", "Roxygen": "list(markdown = TRUE)", "Config/Needs/website": "tidyverse/tidytemplate, brulee", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.0.0", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://tidymodels.r-universe.dev", "Date/Publication": "2026-10-01 00:02:10 UTC", "RemoteUrl": "https://github.com/tidymodels/tabby", "RemoteRef": "HEAD", "RemoteSha": "ad4f632c1a2f62d70a554dd2a75f4f47a8093127", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-16 12:39:09 UTC", "User": "root" }, "Author": "Max Kuhn [aut, cre] (ORCID: ),\nEdgar Ruiz [aut],\nPosit Software, PBC [cph, fnd] (ROR: )", 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