xlm-roberta-xlarge doesn't exist
### System Info

from https://huggingface.co/docs/transformers/model_doc/xlm-roberta-xl

`model = XLMRobertaXLForSequenceClassification.from_pretrained("xlm-roberta-xlarge")
`
I can't find xlm-roberta-xlarge on https://huggingface.co/models

there's facebook/xlm-roberta-xl - but this is the raw masked token model and doesn't seem to work with XLMRobertaXLForSequenceClassification, it's missing the classifier head.

model = XLMRobertaForSequenceClassification.from_pretrained("xlm-roberta-large")
works just fine for me

### Who can help?

_No response_

### Information

- [ ] The official example scripts
- [ ] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

from transformers import AutoTokenizer, XLMRobertaXLForSequenceClassification
model = XLMRobertaXLForSequenceClassification.from_pretrained("xlm-roberta-xlarge")

### Expected behavior

I guess xlm-roberta-xlarge should be available, or the docs should be amended..
Hi @Jack000 , thanks for reporting this issue. 

This is indeed odd - the checkpoint being reference doesn't seem to exist. In the original PR adding the model to the library - it seems the [checkpoints were added under the facebook org](https://github.com/huggingface/transformers/pull/13727#pullrequestreview-866391378). It's OK if the checkpoint used in the example doesn't have the weights for the specific head e.g. for [multiple choice for bert we use `bert-base-uncased`](https://huggingface.co/docs/transformers/v4.29.1/en/model_doc/bert#transformers.BertForMultipleChoice). Would you like to open a PR to update the checkpoint? <|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.