Error when using run_generation.py to generate texts with long prompts, specifically for models -XLM and Openai-GPT
# 🐛 Bug

## Information

Model I am using (XLM, OPENAI-GPT):

Language I am using the model on (English):

The problem arises when using:
* [ ] The models to generate texts with long prompts 

The tasks I am working on is:
* [ ] Text generation

## To reproduce

Steps to reproduce the behavior:

1. cd transformers/
python examples/run_generation.py  --model_type xlm --model_name_or_path xlm-mlm-en-2048 \
                                  --prompt "China wants to take a victory lap over its handling of the coronavirus outbreak" \
                                  --repetition 2.2 --k 5 \
                                  --length 500 

2. 
3.

<!-- Error:   RuntimeError: The size of tensor a (513) must match the size of tensor b (512) at non-singleton dimension 3. \
This leads to the next error - RuntimeError: CUDA error: device-side assert triggered.-->

## Expected behavior

<!-- The expected behavior is a generated piece of texts of about 500 words -->

## Environment info
<!-- cd transformers/
python examples/run_generation.py  --model_type xlm --model_name_or_path xlm-mlm-en-2048 \
                                  --prompt "China wants to take a victory lap over its handling of the coronavirus outbreak" \
                                  --repetition 2.2 --k 5 \
                                  --length 500  -->
     
I think the problem is that there is a bug somewhere in the input_embed or input_id or vocabulary because seems to out of index given certain prompts. This may suggest that the vocab list is limited or maybe not. 

- `transformers` version:
- Platform: Google Colab 
- Python version: 3.6.9
- PyTorch version (GPU?): 1.4.0
- Tensorflow version (GPU?): no
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no

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