How to run the tokenizer independently from the model?
Trace one forward pass so that you know which classes and functions are required for a simple forward pass. Usually,
  you only have to reimplement those functions.
Be able to locate the important components of the model: Where is the model's class? Are there model sub-classes,
  e.g. EncoderModel, DecoderModel? Where is the self-attention layer? Are there multiple different attention layers,
  e.g. self-attention, cross-attention...?
How can you debug the model in the original environment of the repo? Do you have to add print statements, can you
  work with an interactive debugger like ipdb, or should you use an efficient IDE to debug the model, like PyCharm?
It is very important that before you start the porting process, that you can efficiently debug code in the original
