Add LUKE
# What does this PR do?

It adds [LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention](https://arxiv.org/abs/2010.01057) by Yamada et al. [EMNLP 2020].

LUKE is similar to RoBERTa, but it adds an entity embedding matrix (500k Wikipedia entities!) and an entity-aware self-attention mechanism to improve performance on several downstream tasks that involve reasoning about entities, such as entity typing and relation classification. It was pre-trained using MLM on both tokens and entities from Wikipedia. 

Credits for this PR go to the original author @ikuyamada, who implemented everything. I've just set up everything he needed (a basic modeling file, configuration, conversion script, test files, etc.), and guided him through the process. 

Models are already on the hub: https://huggingface.co/models?search=studio-ousia

There are 3 head models defined: 
- `LukeForEntityClassification`, for tasks such as entity typing (given an entity in a sentence, classify it), e.g. the [Open Entity dataset](https://www.cs.utexas.edu/~eunsol/html_pages/open_entity.html). 
- `LukeForEntityPairClassification`, for tasks such as relation classification (classifying the relationship between two entities), e.g. the [TACRED dataset](https://nlp.stanford.edu/projects/tacred/).
- `LukeForEntitySpanClassification`, for tasks such as NER (LUKE obtains SOTA on NER! It considers all possible entity spans in a sentence, and then classifies them accordingly), e.g. the CoNLL-2003 dataset. 

To do:
- [x] add model cards (@ikuyamada this means adding READMEs to the models on the hub, you can take [BERT's one](https://huggingface.co/bert-base-uncased) as inspiration)
- [x] upload fine-tuned models to the hub

## Who can review?

@LysandreJik @sgugger 

Original Github conversation on the original repo: https://github.com/studio-ousia/luke/issues/38

Fixes #10700

@LysandreJik @sgugger all comments are addressed, CI is green! Incredible work by the original author. <|||||>Thanks, addressed your comments.

Added LUKE to the README, and added 3 community notebooks. <|||||>Thanks again for all your work on this!