cr=False)
        >>> model = AutoModelForSequenceClassification.from_pretrained("microsoft/layoutlmv3-base")

        >>> dataset = load_dataset("nielsr/funsd-layoutlmv3", split="train")
        >>> example = dataset[0]
        >>> image = example["image"]
        >>> words = example["tokens"]
        >>> boxes = example["bboxes"]

        >>> encoding = processor(image, words, boxes=boxes, return_tensors="pt")
        >>> sequence_label = torch.tensor([1])

        >>> outputs = model(**encoding, labels=sequence_label)
        >>> loss = outputs.loss
        >>> logits = outputs.logits
        ```Nr/