Apply suggestions from code review

Co-authored-by: Simon P. Couch <[email protected]>

R/sparsevctrs.R

@@ -6,8 +6,8 @@
 #' 
 #' Using sparse data for model fitting and prediction shouldn't require any 
 #' additional configurations. Just pass in a sparse matrix such as dgCMatrix 
-#' from the `Matrix` package or a sparse tibble from the `sparsevctrs` package 
-#' to the data argument of the respective [fit()], [fit_xy()], and [predict()].
+#' from the `Matrix` package or a sparse tibble from the sparsevctrs package 
+#' to the data argument of [fit()], [fit_xy()], and [predict()].
 #' 
 #' Models that don't support sparse data will try to convert to non-sparse data 
 #' with warnings. An informative error will be thrown if conversion isn't