tokenizer = LayoutXLMTokenizer.from_pretrained("microsoft/layoutxlm-base")
```
Similar to LayoutLMv2, you can use [LayoutXLMProcessor] (which internally applies
[LayoutLMv2FeatureExtractor] and
[LayoutXLMTokenizer]/[LayoutXLMTokenizerFast] in sequence) to prepare all
data for the model.
As LayoutXLM's architecture is equivalent to that of LayoutLMv2, one can refer to LayoutLMv2's documentation page for all tips, code examples and notebooks.
This model was contributed by nielsr. The original code can be found here.
LayoutXLMTokenizer
[[autodoc]] LayoutXLMTokenizer
    - call
    - build_inputs_with_special_tokens
    - get_special_tokens_mask
    - create_token_type_ids_from_sequences
    - save_vocabulary
LayoutXLMTokenizerFast
[[autodoc]] LayoutXLMTokenizerFast
    - call
LayoutXLMProcessor
