[Python] Renumerate a column in a group [duplicate]

I'm looking for a scalable way to re-numerate groups (in my case cluster number) in a column. Below the current state with Pandas schema.

data = [
["Adam", 1, 22],
["Eddy", 0, 22],
["Boby", 9, 22],
["Timy", 2, 26],
["Carl", 9, 26],
["Anna", 0, 33],
["Paul", 5, 35],
["Mike", 7, 51],
]

current = pd.DataFrame(data,
columns=['name', 'score', 'cluster']
).astype({'name':'string', 'score':'Int64', 'cluster':'Int64'})


current table looks like that:

+----+--------+---------+-----------+
| | name | score | cluster |
|----+--------+---------+-----------|
| 0 | Adam | 1 | 22 |
| 1 | Eddy | 0 | 22 |
| 2 | Boby | 9 | 22 |
| 3 | Timy | 2 | 26 |
| 4 | Carl | 9 | 26 |
| 5 | Anna | 0 | 33 |
| 6 | Paul | 5 | 35 |
| 7 | Mike | 7 | 51 |
+----+--------+---------+-----------+


my desired state would be:

+----+--------+---------+-----------+
| | name | score | cluster |
|----+--------+---------+-----------|
| 0 | Adam | 1 | 1 |
| 1 | Eddy | 0 | 1 |
| 2 | Boby | 9 | 1 |
| 3 | Timy | 2 | 2 |
| 4 | Carl | 9 | 2 |
| 5 | Anna | 0 | 3 |
| 6 | Paul | 5 | 4 |
| 7 | Mike | 7 | 5 |
+----+--------+---------+-----------+


Assume there will be milions of rows and hundreds of clusters. For a very small amount of clusters I can do it by hand but I need a scalable solution. I've tried to iterate over groups after .groupby("cluster") and to assign consecutive numbers but I failed.

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