pipeline does not do truncation on long texts input, error message found
# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): No specified

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

The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X] 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.  I have tried using pipeline on my own purpose, but I realized it will cause errors if I input long sentence on some tasks, it should do truncation automatically, but it does not. And the pipeline function does not take extra argument so we cannot add something like `truncation=True`. Here is an example on sentiment-analysis task:
```python
from transformers import pipeline
nlp  = pipeline('sentiment-analysis')
text = "This is an example"*300
nlp(text)
```
2. The error message is below:
```
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-31-0a8ce849cc29> in <module>()
      2 nlp  = pipeline('sentiment-analysis')
      3 text = "This is an example"*300
----> 4 nlp(text)

11 frames
/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py in embedding(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)
   1722         # remove once script supports set_grad_enabled
   1723         _no_grad_embedding_renorm_(weight, input, max_norm, norm_type)
-> 1724     return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
   1725 
   1726 

IndexError: index out of range in self
```
3. same error on NER task, maybe some other task as well.

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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 3.0.2
- Platform: Google Colab
- Python version:  Python 3.6.9
- PyTorch version (GPU?):1.5.1+cu101, no GPU
- Tensorflow version (GPU?): no
- Using GPU in script?: no 
- Using distributed or parallel set-up in script?: no

Duplicate of #4224