How to use LayoutLMv3 for Document Layout Detection  task?
### System Info

```shell
trasformers = 4.20.1
Models: layoutlmv3

How to use LayoutLMv3 for Document Layout Detection, for example microsoft unilm(https://github.com/microsoft/unilm/tree/master/layoutlmv3)?
I do not find Document Layout Detection task infomation in example and modeling.
The typical dataset for Document Layout Detection is call PubLayNet (https://github.com/ibm-aur-nlp/PubLayNet).


example :https://github.com/huggingface/transformers/tree/main/examples/research_projects/layoutlmv3
modeling: https://github.com/huggingface/transformers/tree/main/src/transformers/models/layoutlmv3
```


### Who can help?

_No response_

### Information

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

### Tasks

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

### Reproduction

How to use LayoutLMv3 for Document Layout Detection, for example microsoft unilm(https://github.com/microsoft/unilm/tree/master/layoutlmv3)?
I do not find Document Layout Detection task infomation in example and modeling.
The typical dataset for Document Layout Detection is call PubLayNet (https://github.com/ibm-aur-nlp/PubLayNet).

### Expected behavior

```shell
I can know how to use layoutlmv3 model in transformers for  Document Layout Detection?
I would really appreciate it if you can give me an example code.
```

Hi,

If you read a bit more closely: https://github.com/microsoft/unilm/tree/master/layoutlmv3#document-layout-analysis-on-publaynet

You'll see they provide a guide regarding fine-tuning LayoutLMv3 on PubLayNet. The Mask R-CNN framework is leveraged. This framework currently is not available in Huggingface Transformers, so you'll need to use the unilm repo for that.<|||||>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.