Loading pretrained mBART model always generate the same output
Hi,

I trained mBART with pytorch lightning with the model MBartForConditionalGeneration.from_pretrained('facebook/mbart-large-cc25') to do summaries.  As output I got a checkpoint.ckpt. Moreover, I used model.model.save_pretrained to have a config.json and pytorch_model.bin. 
During the training and testing, I saw what the model was generating as summaries and I got satisfying results. 
However, when I load it back into transformers, the output it generates is always the same no matter the input. I can see that this output comes from my training data but during the training and testing the model was not doing this. The model was in fact generating output with a relation to the input which is not the case here as it always outputs the same thing. 
I suppose there must be a mistake on how I load and use the pretrained model but I don't know what. 
This is how I do it: 

```
configuration = MBartConfig.from_json_file("config.json")
model = MBartForConditionalGeneration.from_pretrained("pytorch_model.bin",
config="configuration")
tokenizer = MBartTokenizer.from_pretrained('facebook/mbart-large-cc25')
inputs = tokenizer([ARTICLE_TO_SUMMARIZE], max_length=1024, return_tensors='pt')
summary_ids = model.generate(inputs['input_ids'], num_beams=4, max_length=150, early_stopping=True)
print([tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=False) for g in summary_ids])
```


Thanks in advance for the help