How to fine-tune T5 with some additional special tokens ?
I wanna to fine-tune T5 with seq2seq task, but there are some special tokens in this seq2seq task. T5 performs bad without these tokens.  How could I use some additional special tokens to fine-tune T5 with scripts https://github.com/huggingface/transformers/blob/master/examples/seq2seq/finetune_t5.sh?





Let's say the tokens you want to add are <some_token_1> and <some_token_2> (including angle brackets)
```
from transformers import T5Tokenizer
tokenizer = T5Tokenizer.from_pretrained("t5-base")
tokenizer.add_tokens(['<some_token_1>', '<some_token_2'>])
```<|||||>I want to add this line in addition to modifying the tokenizer for the model to work with the new tokenizer:

`model.resize_token_embeddings(len(tokenizer))`