single forward pass using a dummy integer vector of input IDs as an input. Such a script could look like this (in
pseudocode):
python
model = BrandNewBertModel.load_pretrained_checkpoint("/path/to/checkpoint/")
input_ids = [0, 4, 5, 2, 3, 7, 9]  # vector of input ids
original_output = model.predict(input_ids)
Next, regarding the debugging strategy, there are generally a few from which to choose from:
Decompose the original model into many small testable components and run a forward pass on each of those for
  verification
Decompose the original model only into the original tokenizer and the original model, run a forward pass on
  those, and use intermediate print statements or breakpoints for verification
Again, it is up to you which strategy to choose. Often, one or the other is advantageous depending on the original code
