theoretical aspects, but rather focus on the practical ones, namely:
What type of model is brand_new_bert? BERT-like encoder-only model? GPT2-like decoder-only model? BART-like
  encoder-decoder model? Look at the model_summary if you're not familiar with the differences between those.
What are the applications of brand_new_bert? Text classification? Text generation? Seq2Seq tasks, e.g.,
  summarization?
What is the novel feature of the model making it different from BERT/GPT-2/BART?
Which of the already existing 🤗 Transformers models is most
  similar to brand_new_bert?
What type of tokenizer is used? A sentencepiece tokenizer? Word piece tokenizer? Is it the same tokenizer as used
  for BERT or BART?
After you feel like you have gotten a good overview of the architecture of the model, you might want to write to the
