Typo in Pegasus model usage example
Author: albertovilla
Pull request: no

## Environment info
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     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.6.1
- Platform: Linux-5.4.109+-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.10
- PyTorch version (GPU?): 1.8.1+cu101 (True)
- Tensorflow version (GPU?): 2.5.0 (True)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: No

### Who can help
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Documentation: @sgugger

## Information

Model I am using (Bert, XLNet ...): Pegasus

The problem arises when using:
* [x] the official example 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): just trying the Pegasus model

## To reproduce

Steps to reproduce the behavior:

1. Create a new Colab notebook and install the required libraries using:
```python
!pip install transformers
!pip install sentencepiece
```
2. Copy / paste the "Usage example" from the pegasus [documentation](https://huggingface.co/transformers/model_doc/pegasus.html) page in a cell:

```python
from transformers import PegasusForConditionalGeneration, PegasusTokenizer
import torch

src_text = [
     """ PG&E stated it scheduled the blackouts in response to forecasts for high winds amid dry conditions. The aim is to reduce the risk of wildfires. Nearly 800 thousand customers were scheduled to be affected by the shutoffs which were expected to last through at least midday tomorrow."""
]

model_name = 'google/pegasus-xsum'
device = 'cuda' if torch.cuda.is_available() else 'cpu'

tokenizer = PegasusTokenizer.from_pretrained(model_name)
model = PegasusForConditionalGeneration.from_pretrained(model_name).to(device)

batch = tokenizer(src_text, truncation=True, padding='longest', return_tensors="pt").to(device)
translated = model.generate(**batch)
tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)

assert tgt_text[0] == "California's largest electricity provider has turned off power to hundreds of thousands of customers."
```

3. Execute the cell

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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->

The final statement `assert`  should be True, however there is an typo en the usage example and we get an error:

```python
12 model = PegasusForConditionalGeneration.from_pretrained(model_name).to(device)
     13 
---> 14 batch = tokenizer(src_text, truncation=True, padding='longest', return_tensors="pt").to(torch_device)
     15 translated = model.generate(**batch)
     16 tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)

NameError: name 'torch_device' is not defined
```

The reason of the above error is that one of the lines of the code is referring to `torch_device` when it should refer to `device`. Change the line 
- ```python batch = tokenizer(src_text, truncation=True, padding='longest', return_tensors="pt").to(torch_device)```
To the following:
- ```python batch = tokenizer(src_text, truncation=True, padding='longest', return_tensors="pt").to(device)```

 



Comments:
Thanks for flagging this! Would you mind sending a PR with the fix since you found it?

Hi @sgugger, I have just created a PR. 
Kind regards

Thanks!
Closed by #11979