Encoding string labels to integers for hierarchical mutli-class classification

Question

Currently working on a hierarchical classification task, where I give my model some text input and it tells me, which 3 categories it belongs to (main category, sub category, leaf category).

My labels are currently a list of strings, but for my model I need them as integers between 0 to N-1 (N being the number of classes in this category level).

I managed to find a solution by using a dictionary and giving each string a number (encoding) and then another dictionary doing the opposite (decoding) to check what the predictions are.

It works, but I figured once I use another dataset, I would have to generate two dictionaries again. I looked around and found these two classes from the sklearn preprocessing library: MultiLabelBinarizer() and LabelEncoder(). It looks like what I would need, but I have no idea how to use it in combination with the hierarchies.

Would appreciate any kind of hints on how to use them or any other solution!