[CLS] And the very very last one [SEP] And I go with the very last one [SEP]
```
Once again, you can automatically pad your inputs to the maximum sentence length in the batch, truncate to the maximum
length the model can accept and return tensors directly with the following:
py
batch = tokenizer(batch_sentences, batch_of_second_sentences, padding=True, truncation=True, return_tensors="pt")
===PT-TF-SPLIT===
batch = tokenizer(batch_sentences, batch_of_second_sentences, padding=True, truncation=True, return_tensors="tf")
Everything you always wanted to know about padding and truncation
We have seen the commands that will work for most cases (pad your batch to the length of the maximum sentence and
truncate to the maximum length the model can accept). However, the API supports more strategies if you need them. The
