) loss. Input should be a sequence pair
            (see `input_ids` docstring) Indices should be in `[0, 1]`.

            - 0 indicates sequence B is a continuation of sequence A,
            - 1 indicates sequence B is a random sequence.

        Returns:

        Examples:

        ```python
        >>> from transformers import AutoTokenizer, MobileBertForNextSentencePrediction
        >>> import torch

        >>> tokenizer = AutoTokenizer.from_pretrained("google/mobilebert-uncased")
        >>> model = MobileBertForNextSentencePrediction.from_pretrained("google/mobilebert-uncased")

        >>> prompt = "In Italy, pizza served in formal settings, such as at a restaurant, is presented unsliced."
        >>> next_sentence = "The sky is blue due to the shorter wavelength of blue light."
        >>> encoding = tokenizer(prompt, next_sentence, return_tensors="pt")

        >>> outputs = model(**encoding, labels=torch.LongTensor([1]))
        >>> loss = outputs.loss
        >>> logits = outputs.logits
        ```rA