The pytorch example summarization/run_summarization.py do not work with MBart
## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: git+https://github.com/huggingface/transformers
- Platform:
- Python version: 3.8
- PyTorch version (GPU?): 1.10.0
- Using GPU in script?: yes
- Using GPU in script?:
- Using distributed or parallel set-up in script?:

### Who can help

@sgugger @NielsRogge @Narsil @patrickvonplaten 

Models:

- MBart: facebook/mbart-large-cc25
- encoder-decoder models (For example, BlenderBot, BART, Marian, Pegasus, T5, ByT5): facebook/mbart-large-cc25
- Pytorch: 1.10.0

If the model isn't in the list, ping @LysandreJik who will redirect you to the correct contributor.

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)


Examples:

- maintained examples (not research project or legacy): [summarization/run_summarization.py](https://github.com/huggingface/transformers/blob/master/examples/pytorch/summarization/run_summarization.py)


## Information

Model I am using (Bert, XLNet ...): MBart

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [x] an official GLUE/SQUaD task: (give the name): summarization
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. run the  [summarization/run_summarization.py](https://github.com/huggingface/transformers/blob/master/examples/pytorch/summarization/run_summarization.py) with facebook/mbart-large-cc25 as model
2. receive the error:
```
INFO|tokenization_utils_base.py:888] 2021-11-10 17:36:01,873 >> Assigning ['ar_AR', 'cs_CZ', 'de_DE', 'en_XX', 'es_XX', 'et_EE', 'fi_FI', 'fr_XX', 'gu_IN', 'hi_IN', 'it_IT', 'ja_XX', 'kk_KZ', 'ko_KR', 'lt_LT', 'lv_LV', 'my_MM', 'ne_NP', 'nl_XX', 'ro_RO', 'ru_RU', 'si_LK', 'tr_TR', 'vi_VN', 'zh_CN'] to the additional_special_tokens key of the tokenizer
[INFO|modeling_utils.py:1342] 2021-11-10 17:36:02,289 >> loading weights file https://huggingface.co/facebook/mbart-large-cc25/resolve/main/pytorch_model.bin from cache at /home/super/.cache/huggingface/transformers/58963b41815ac5618d9910411e018d60a3ae7d4540a66e6cf70adf29a748ca1b.bef0d2e3352d6c4bf1213c6207738ec5ecf458de355c65b2aead6671bc612138
[INFO|modeling_utils.py:1609] 2021-11-10 17:36:07,745 >> All model checkpoint weights were used when initializing MBartForConditionalGeneration.

 

[INFO|modeling_utils.py:1617] 2021-11-10 17:36:07,745 >> All the weights of MBartForConditionalGeneration were initialized from the model checkpoint at facebook/mbart-large-cc25.
If your task is similar to the task the model of the checkpoint was trained on, you can already use MBartForConditionalGeneration for predictions without further training.
Traceback (most recent call last):
  File "src/run_summarization_bart.py", line 645, in <module>
    main()
  File "src/run_summarization_bart.py", line 371, in main
    raise ValueError("Make sure that `config.decoder_start_token_id` is correctly defined")
ValueError: Make sure that `config.decoder_start_token_id` is correctly defined
```

MBart is in the list of model to use with this script, but this multilingual model seams different.

## Expected behavior

Train summarization with pre-trained MBart correctly.

Good point! @patil-suraj - let's try to fix this :-)<|||||>@sgugger @patrickvonplaten  @patil-suraj  any news about the problem?<|||||>I also faced the same problem, @patrickvonplaten, @patil-suraj, any news? :)<|||||>Sorry about the super late response.

We will need to support the language codes for mBART as we do in the `run_translation.py` script. Will update the script in a couple of days or feel free to open a PR @nicolalandro @banda-larga  if you want, happy to help with it :) <|||||>Hi @patrickvonplaten @patil-suraj 
Do you have any updates on the mbart compatibility? Appreciate that you are looking into this. Thank you very much. <|||||>Sorry about being late here again, will try to add it this week :) Thanks!<|||||>Hi @patil-suraj . Is there an update on this? Thanks!<|||||>Hey @Nikoschenk, messed up my schedule again! Sorry about the delay. I will take a look at it this week for sure <|||||>The `run_summarization.py` now supports `mBART` thanks to @banda-larga !
Fixed by #15125<|||||>@banda-larga @patil-suraj thank you very much! That‘s great. 