QA pipeline fails with long context. 
## Environment info
- `transformers` version: 3.0.2n your GitHub issue and FILL OUT the two last points.
- Platform: Linux-4.15.0-117-generic-x86_64-with-glibc2.10
- Python version: 3.8.2
- PyTorch version (GPU?): 1.4.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Same result either way
- Using distributed or parallel set-up in script?: no

### Who can help

@sgugger

## Information

Model I am using: DistilBert via the QA pipeline. 

The tasks I am working on is:
* my own task or dataset:

## To reproduce

```
from transformers import pipeline
nlp = pipeline("question-answering")
context = """
Once upon a midnight dreary, while I pondered, weak and weary,
Over many a quaint and curious volume of forgotten lore—
    While I nodded, nearly napping, suddenly there came a tapping,
As of some one gently rapping, rapping at my chamber door.
“’Tis some visitor,” I muttered, “tapping at my chamber door—
            Only this and nothing more.”

    Ah, distinctly I remember it was in the bleak December;
And each separate dying ember wrought its ghost upon the floor.
    Eagerly I wished the morrow;—vainly I had sought to borrow
    From my books surcease of sorrow—sorrow for the lost Lenore—
For the rare and radiant maiden whom the angels name Lenore—
            Nameless here for evermore.

    And the silken, sad, uncertain rustling of each purple curtain
Thrilled me—filled me with fantastic terrors never felt before;
    So that now, to still the beating of my heart, I stood repeating
    “’Tis some visitor entreating entrance at my chamber door—
Some late visitor entreating entrance at my chamber door;—
            This it is and nothing more.”

    Presently my soul grew stronger; hesitating then no longer,
“Sir,” said I, “or Madam, truly your forgiveness I implore;
    But the fact is I was napping, and so gently you came rapping,
    And so faintly you came tapping, tapping at my chamber door,
That I scarce was sure I heard you”—here I opened wide the door;—
            Darkness there and nothing more.

    Deep into that darkness peering, long I stood there wondering, fearing,
Doubting, dreaming dreams no mortal ever dared to dream before;
    But the silence was unbroken, and the stillness gave no token,
    And the only word there spoken was the whispered word, “Lenore?”
This I whispered, and an echo murmured back the word, “Lenore!”—
            Merely this and nothing more.

    Back into the chamber turning, all my soul within me burning,
Soon again I heard a tapping somewhat louder than before.
    “Surely,” said I, “surely that is something at my window lattice;
      Let me see, then, what thereat is, and this mystery explore—
Let my heart be still a moment and this mystery explore;—
            ’Tis the wind and nothing more!”
"""
nlp(question="What is the month?", context=context)

/home/brian/transformers/src/transformers/tokenization_utils_base.py:1292: FutureWarning: The `max_len` attribute has been deprecated and will be removed in a future version, use `model_max_length` instead.
  warnings.warn(
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-8-d64d967fe1dd> in <module>
----> 1 nlp(question="What is the month?", context=context)

~/transformers/src/transformers/pipelines.py in __call__(self, *args, **kwargs)
   1636                     with torch.no_grad():
   1637                         # Retrieve the score for the context tokens only (removing question tokens)
-> 1638                         fw_args = {k: torch.tensor(v, device=self.device) for (k, v) in fw_args.items()}
   1639                         start, end = self.model(**fw_args)[:2]
   1640                         start, end = start.cpu().numpy(), end.cpu().numpy()

~/transformers/src/transformers/pipelines.py in <dictcomp>(.0)
   1636                     with torch.no_grad():
   1637                         # Retrieve the score for the context tokens only (removing question tokens)
-> 1638                         fw_args = {k: torch.tensor(v, device=self.device) for (k, v) in fw_args.items()}
   1639                         start, end = self.model(**fw_args)[:2]
   1640                         start, end = start.cpu().numpy(), end.cpu().numpy()

ValueError: expected sequence of length 384 at dim 1 (got 379)
```

## Expected behavior

```
{'score': 0.9419336915016174, 'start': 401, 'end': 410, 'answer': 'December;'}
```
This was fixed in a more recent version.