n/xprophetnet-large-uncased-standalone"
        ... )

        >>> input_ids = tokenizer(
        ...     "Studies have been shown that owning a dog is good for you", return_tensors="pt"
        ... ).input_ids  # Batch size 1
        >>> decoder_input_ids = tokenizer("Studies show that", return_tensors="pt").input_ids  # Batch size 1
        >>> outputs = model(input_ids=input_ids, decoder_input_ids=decoder_input_ids)

        >>> logits_next_token = outputs.logits  # logits to predict next token as usual
        >>> logits_ngram_next_tokens = outputs.logits_ngram  # logits to predict 2nd, 3rd, ... next tokens
        ```N)r„