Question 4
Consider the following Python code snippet using Hugging Face tokenizers:
from tokenizers import Tokenizerfrom tokenizers.models import BPEfrom tokenizers.pre_tokenizers import Whitespacefrom tokenizers.normalizers import Lowercasefrom tokenizers.processors import TemplateProcessing
tokenizer = Tokenizer(BPE(unk_token="[UNK]"))tokenizer.normalizer = Lowercase()tokenizer.pre_tokenizer = Whitespace()
tokenizer.post_processor = TemplateProcessing( single="[CLS] $A [SEP]", pair="[CLS] $A [SEP] $B:1 [SEP]:1", special_tokens=[("[CLS]", tokenizer.token_to_id("[CLS]")), ("[SEP]", tokenizer.token_to_id("[SEP]"))],)encoded_output = tokenizer.encode("Hello World")Which of the following attributes would be present in the encoded_output object and directly reflect the action of the TemplateProcessing post-processor for a single sequence as configured?