MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50") Not working
## Environment info
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     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.5.0
- Platform: anaconda
- Python version: 3.7
- PyTorch version (GPU?): 1.1.0
- Tensorflow version (GPU?): 
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

### Who can help
@patrickvonplaten 


Models:
 MBart50


## Information

Model I am using (Bert, XLNet ...):
MBart50
The problem arises when using:
Official script as in https://huggingface.co/transformers/master/model_doc/mbart.html#transformers.MBart50Tokenizer

The tasks I am working on is:
Official summarization task

## To reproduce

Steps to reproduce the behavior:

1. from transformers import MBartForConditionalGeneration, MBart50TokenizerFast
2. model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50")

Error:
                                                                                                                                                       File "/home/aniruddha/anaconda3/envs/rupak_qg/lib/python3.6/site-packages/transformers/modeling_utils.py", line 1066, in from_pretrained                                                       f"Unable to load weights from pytorch checkpoint file for '{pretrained_model_name_or_path}' "                                                                                            OSError: Unable to load weights from pytorch checkpoint file for 'facebook/mbart-large-50' at '/home/aniruddha/.cache/huggingface/transformers/66cec75cd01a09243232a4dbb6e99525d2571fd2c73870343ad4573df28f5924.e61a75127adcaf4f5c0903618b64b779413423b5f661ece62a4839582b2b850a'If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True. 

## Expected behavior

The model should load correctly.

I can load the model without any issues, I think the issue here is the `from_pretrained` call is hitting the cache and the model is not cached properly. You could force the download by passing `force_download=True`

```python
model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50", force_download=True)
```<|||||>I am also still facing the problem, can you please mention if there is verson specific<|||||>but is is successfully loading for BART-large model
 <|||||>You could try deleting the cache in that case.<|||||>Not happening aging, same error is coming
<|||||>See this [colab](https://colab.research.google.com/drive/1ENrFbZIxmK0ZtrtUduCADEZDZtg_QKZT?usp=sharing) it uses 4.5.0 and can load mbart. <|||||>> I can load the model without any issues, I think the issue here is the `from_pretrained` call is hitting the cache and the model is not cached properly. You could force the download by passing `force_download=True`
> 
> ```python
> model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50", force_download=True)
> ```

Hi, do you know how to run transformer model like t5-small, facebook/bart-large-cnn without loading pre-trained weights?  When using run_summarization.py, I only want to train their original model architecture without pre-trained model. Thank you very much!
<|||||>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.

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