[LukeTokenizer] has a task argument, which enables you to easily create an input to these
  head models by specifying task="entity_classification", task="entity_pair_classification", or
  task="entity_span_classification". Please refer to the example code of each head models.
A demo notebook on how to fine-tune [LukeForEntityPairClassification] for relation
  classification can be found here.
There are also 3 notebooks available, which showcase how you can reproduce the results as reported in the paper with
  the HuggingFace implementation of LUKE. They can be found here.
Example:
```python
from transformers import LukeTokenizer, LukeModel, LukeForEntityPairClassification
model = LukeModel.from_pretrained("studio-ousia/luke-base")
tokenizer = LukeTokenizer.from_pretrained("studio-ousia/luke-base")
