TypeError when using Feature Extraction Pipeline with XLM roberta
# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): XLM-R

Language I am using the model on (English, Chinese ...): English

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [x] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. after importing the required libraries, run the following snipped of code:
```
xlmr_model = XLMRobertaForSequenceClassification.from_pretrained("xlm-roberta-base")
xlmr_tokenizer = XLMRobertaTokenizer.from_pretrained("xlm-roberta-base")
nlp = pipeline(task ="feature-extraction", model = xlmr_model, tokenizer=xlmr_tokenizer, framework="tf")
features = nlp('We are very happy to include pipeline into the transformers repository.')
print(features)
```
2. You should get the following error: result = self.forward(*input, **kwargs)
**TypeError: forward() got an unexpected keyword argument 'training'**

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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->
I would expect this code to run without this error.

## Environment info
<!-- You can run the command `python transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 2.6.1
- Platform: Ubuntu 16.04.6 LTS
- Python version: 3.6.1
- PyTorch version (GPU?): No GPU
- Tensorflow version (GPU?): No GPU
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No
