The tokenizer returns a dictionary containing:

input_ids: numerical representations of your tokens.
attention_mask: indicates which tokens should be attended to.

A tokenizer can also accept a list of inputs, and pad and truncate the text to return a batch with uniform length:

pt_batch = tokenizer(
     ["We are very happy to show you the 🤗 Transformers library.", "We hope you don't hate it."],
     padding=True,
     truncation=True,
     max_length=512,
     return_tensors="pt",
 )