TrOCR comment change
Thanks for the TrOCR modules @NielsRogge !

I noticed something very small in one of the comments - if you copy pasted the lines from the comment block, they wouldn't work, because the default image size in `ViTConfig` is 224, while the `processor` is expecting the image to be resized to 384x384. 
_The documentation is not available anymore as the PR was closed or merged._<|||||>Hi,

Thanks for your PR! We actually test that code snippet as TrOCR is [included in the doc tests](https://github.com/huggingface/transformers/blob/b29e2dcaff114762e65eaea739ba1076fc5d1c84/utils/documentation_tests.txt#L190). So the code runs fine. Of course, if you would use that model in combination with TrOCRProcessor, you would have to instantiate the image processor's size to be {"height": 224, "width": 224}, like so:

```
from transformers import RobertaTokenizer, ViTImageProcessor, TrOCRProcessor, ViTConfig, TrOCRConfig, VisionEncoderDecoderModel

tokenizer =  RobertaTokenizer.from_pretrained("roberta-base")
image_processor = ViTImageProcessor(size={"height": 224, "width": 224})
processor = TrOCRProcessor(tokenizer=tokenizer, image_processor=image_processor)

config_encoder = ViTConfig()
config_decoder = TrOCRConfig()

config = VisionEncoderDecoderConfig.from_encoder_decoder_configs(config_encoder, config_decoder)
model = VisionEncoderDecoderModel(config=config)
```<|||||>Thanks for your quick reply! 

I believe that particular bit of code in the docstring runs fine because `model` gets overwritten a couple of lines below it. Do you think it is worth it to put the lines of code you've written in your comment in the docstring as well in case someone wants to try to train a model without the weights from microsoft? 

If not, it's not a big deal, I'll just close this PR.