Package: dragonfarm
Title: Fine-Tune Small Language Models with LoRA from R
Version: 0.3.3
Authors@R: 
    person("Tejas", "Patel", role = c("aut", "cre"), email = "algocrat@gmail.com")
Description: Fine-tune small (100M to 3B parameter) causal language models
    with LoRA (Low-Rank Adaptation) from R. Datasets are mapped to
    chat-format prompts and responses, training runs in a background
    'Python' process built on Hugging Face 'transformers' and 'peft', and a
    'shiny' app offers drag-and-drop dataset upload and column mapping.
    'Python' dependencies are declared through 'reticulate' and resolved
    automatically on first use.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: bslib (>= 0.6.0), cli, glue, jsonlite, plotly, processx, ps,
        reticulate (>= 1.41.0), rlang, shiny (>= 1.8.0), sortable,
        stats, tools, utils, withr, zip
Suggests: arrow, ellmer, httr2, knitr, pkgload, rmarkdown, testthat (>=
        3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
SystemRequirements: 'Python' (>= 3.10). The 'uv' tool is installed
        automatically by 'reticulate' to build the 'Python'
        environment.
URL: https://github.com/tejas4patel/dragon-farm
BugReports: https://github.com/tejas4patel/dragon-farm/issues
Config/roxygen2/version: 8.1.0
NeedsCompilation: no
Packaged: 2026-09-27 23:49:15 UTC; Tejas
Author: Tejas Patel [aut, cre]
Maintainer: Tejas Patel <algocrat@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-07 09:50:22 UTC
Built: R 4.5.3; ; 2026-10-07 14:20:02 UTC; windows
