RobertaForMaskedLM Failing for example code given on Hugging Face' documentation page
# 🐛 Bug

from transformers import RobertaTokenizer, RobertaForMaskedLM
import torch

tokenizer = RobertaTokenizer.from_pretrained('roberta-base')
model = RobertaForMaskedLM.from_pretrained('roberta-base')
input_ids = torch.tensor(tokenizer.encode("Hello, my dog is cute", add_special_tokens=True)).unsqueeze(0)  # Batch size 1
outputs = model(input_ids, labels=input_ids)
loss, prediction_scores = outputs[:2]

I am using this example code given on hugging face's documentation page , but this also gives an error 
TypeError: forward() got an unexpected keyword argument 'labels'

The doc clearly states that forward accepts labels ,what's wrong here?
Which version of the library are you using? The documentation corresponds to the master branch and the change in the argument names was pretty recent, so I don't think it's in the latest release yet. You should either [install from source](https://github.com/huggingface/transformers#from-source) or change the code to use the (soon-to-be deprecated) argument `masked_lm_labels` (see the documentation for the latest release [here](https://huggingface.co/transformers/v2.5.0/model_doc/bert.html#bertformaskedlm)).<|||||>Thank you @sgugger for the latest documentation. I reinstalled transformers again yesterday sO I guess I am using latest version
 I was scratching my head due to this