```python
from transformers import LukeModel
model = LukeModel.from_pretrained("studio-ousia/mluke-base")
```
Note that mLUKE has its own tokenizer, [MLukeTokenizer]. You can initialize it as follows:
```python
from transformers import MLukeTokenizer
tokenizer = MLukeTokenizer.from_pretrained("studio-ousia/mluke-base")
```
As mLUKE's architecture is equivalent to that of LUKE, one can refer to LUKE's documentation page for all
tips, code examples and notebooks.
This model was contributed by ryo0634. The original code can be found here.
MLukeTokenizer
[[autodoc]] MLukeTokenizer
    - call
    - save_vocabulary
