The trick here is to create a random variable, sort the dataset by that random variable,
and then assign the observations to the groups. Let’s use the hsb2 dataset as an example by
randomly assigning 50 observations to each of four groups.

use https://stats.idre.ucla.edu/stat/stata/notes/hsb2, clear

set seed 12345
generate rannum = uniform()
sort rannum
generate grp = .
replace grp = 0 in 1/50
replace grp = 1 in 51/100
replace grp = 2 in 101/150
replace grp = 3 in 151/200

tabulate grp

        grp |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         50       25.00       25.00
          1 |         50       25.00       50.00
          2 |         50       25.00       75.00
          3 |         50       25.00      100.00
------------+-----------------------------------
      Total |        200      100.00
      
sort id
clist id grp in 1/20

            id        grp
  1.         1          0
  2.         2          3
  3.         3          2
  4.         4          1
  5.         5          0
  6.         6          3
  7.         7          1
  8.         8          2
  9.         9          0
 10.        10          0
 11.        11          1
 12.        12          0
 13.        13          3
 14.        14          0
 15.        15          3
 16.        16          3
 17.        17          3
 18.        18          1
 19.        19          3
 20.        20          3

Of course, when you try this the grp number for each id will be in a different pattern
because we are using a random process to assign observations to groups.

It is possible to make the code even simpler then the above by using the egen , cut()
command.

use https://stats.idre.ucla.edu/stat/stata/notes/hsb2, clear

generate rannum = uniform()
egen grp2 = cut(rannum), group(4)

sort id
list id grp2 in 1/20

            id       grp2
  1.         1          0
  2.         2          3
  3.         3          2
  4.         4          1
  5.         5          0
  6.         6          3
  7.         7          1
  8.         8          2
  9.         9          0
 10.        10          0
 11.        11          1
 12.        12          0
 13.        13          3
 14.        14          0
 15.        15          3
 16.        16          3
 17.        17          3
 18.        18          1
 19.        19          3
 20.        20          3

For more information see the Stata manual or Stata Help for
functions.