Adding mbart-large-cc25
# 🌟 New model addition
Multilingual BART model implemented in fairseq introduced by FAIR

## Model description
This issue is to request adding mBART model existing as a part of fairseq lib. 

[Link to the fairseq description of the model](https://github.com/pytorch/fairseq/tree/master/examples/mbart
)
[Link to the mBART paper](https://arxiv.org/abs/2001.08210)

Multilingually pretrained BART checkpoint.

<!-- Important information -->
The model code follows the original BART model code which is already a part of ```transformers``` repo. However, it introduces a couple more features like multilingual denoising and translation from pretrained BART. 

## Open source status

- [x] _the model implementation is available: (give details)_
[Link to the PR adding mBART to the fairseq](https://github.com/pytorch/fairseq/commit/5e79322b3a4a9e9a11525377d3dda7ac520b921c) 
This PR shows the main pieces that were added to the fairseq to make mBART work considering BART  which is already existing in the codebase. However, a few additional mBART commits were added afterward.

- [x] _the model weights are available: (give details)_
[Link to the weights](https://github.com/pytorch/fairseq/tree/master/examples/mbart#pre-trained-models)

- [x] _who are the authors: (mention them, if possible by @gh-username)_
Facebook AI Research (@MultiPath)
This is a Work in progress but still a few weeks out :)<|||||>Hi @sshleifer , additional (perhaps bug, or document bug) related to this issue: 

This model page suggests that we can load mBart-cc25 : 
https://huggingface.co/facebook/mbart-large-cc25

However, using the instructed command with the newest HuggingFace 2.8.0 : 
`model =  AutoModel.from_pretrained("facebook/mbart-large-cc25")`

is failed :
```
AttributeError: 'NoneType' object has no attribute 'seek'. You can only torch.load from a file that is seekable. Please pre-load the data into a buffer like io.BytesIO and try to load from it instead.

During handling of the above exception, another exception occurred:

OSError                                   Traceback (most recent call last)
<ipython-input-4-c034f52e2196> in <module>
     11 '''
     12 
---> 13 model =  AutoModel.from_pretrained("facebook/mbart-large-cc25")
     14 tokenizer = AutoTokenizer.from_pretrained("facebook/mbart-large-cc25")

/opt/conda/lib/python3.7/site-packages/transformers/modeling_auto.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    421         for config_class, model_class in MODEL_MAPPING.items():
    422             if isinstance(config, config_class):
--> 423                 return model_class.from_pretrained(pretrained_model_name_or_path, *model_args, config=config, **kwargs)
    424         raise ValueError(
    425             "Unrecognized configuration class {} for this kind of AutoModel: {}.\n"

/opt/conda/lib/python3.7/site-packages/transformers/modeling_utils.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
    625             except Exception:
    626                 raise OSError(
--> 627                     "Unable to load weights from pytorch checkpoint file. "
    628                     "If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True. "
    629                 )

OSError: Unable to load weights from pytorch checkpoint file. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True. 
```<|||||>Yes, the docs are wrong/aspirational at the moment. Will fix today!<|||||>Fixed the docs. That model is currently not supported, but it's on my roadmap to add it in the coming weeks.<|||||>sshleifer, wonder if the mbart-large-cc25 have been added? We are looking to use mbart for a multilingual text classification problem. Thanks for the great work.
Patrick<|||||>Hopefully this weekend!<|||||>What languages are you trying to support?
We have 1,000+ models in the `MarianMTModel` family, 11 of which are multi-lingual.
<|||||>We are blocked for the moment on https://github.com/pytorch/fairseq/issues/2258, 
if anybody has any ideas how to fix that it would be much appreciated!

