  running the forward pass, e.g. check-out this link.
Use the smallest pretrained checkpoint you can find. The smaller the checkpoint, the faster your debug cycle
  becomes. It is not efficient if your pretrained model is so big that your forward pass takes more than 10 seconds.
  In case only very large checkpoints are available, it might make more sense to create a dummy model in the new
  environment with randomly initialized weights and save those weights for comparison with the 🤗 Transformers version
  of your model
Make sure you are using the easiest way of calling a forward pass in the original repository. Ideally, you want to
  find the function in the original repository that only calls a single forward pass, i.e. that is often called
  predict, evaluate, forward or __call__. You don't want to debug a function that calls forward
