Unable to load pipeline for question answering
## 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: 2.11.0
- Platform: Linux-4.19.112+-x86_64-with-debian-buster-sid
- Python version: 3.7.6
- PyTorch version (GPU?): 1.5.1 (False)
- Tensorflow version (GPU?): 2.3.0 (False)
- Using GPU in script?: <fill in>
- Using distributed or parallel set-up in script?: <fill in>

### Who can help
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 Please tag fewer than 3 people.
 
 albert, bert, GPT2, XLM: @LysandreJik 
 tokenizers: @mfuntowicz
 examples/distillation: @VictorSanh
 documentation: @sgugger
 -->

## Information

Model I am using pipeline for question answering:

The problem arises when using:
* [ ] the official example scripts: (give details below)
from transformers import pipeline
nlp_qa = pipeline('question-answering')


## To reproduce

Steps to reproduce the behavior:

1. Ran the below snippet on kaggle
```
from transformers import pipeline
nlp_qa = pipeline('question-answering')
```

### Error message I got
```
OSError: Can't load config for 'distilbert-base-cased'. Make sure that:

- 'distilbert-base-cased' is a correct model identifier listed on 'https://huggingface.co/models'

- or 'distilbert-base-cased' is the correct path to a directory containing a config.json file

```
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### Full error 
```
---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
/opt/conda/lib/python3.7/site-packages/transformers/configuration_utils.py in get_config_dict(cls, pretrained_model_name_or_path, **kwargs)
    242             if resolved_config_file is None:
--> 243                 raise EnvironmentError
    244             config_dict = cls._dict_from_json_file(resolved_config_file)

OSError: 

During handling of the above exception, another exception occurred:

OSError                                   Traceback (most recent call last)
<ipython-input-24-a978a087c38f> in <module>
      1 from transformers import pipeline
      2 
----> 3 nlp_qa = pipeline('question-answering') # 1st try
      4 # nlp_qa = pipeline('question-answering', model=model, tokenizer = tokenizer, device=torch.cuda.current_device())

/opt/conda/lib/python3.7/site-packages/transformers/pipelines.py in pipeline(task, model, config, tokenizer, framework, **kwargs)
   1787         if isinstance(tokenizer, tuple):
   1788             # For tuple we have (tokenizer name, {kwargs})
-> 1789             tokenizer = AutoTokenizer.from_pretrained(tokenizer[0], **tokenizer[1])
   1790         else:
   1791             tokenizer = AutoTokenizer.from_pretrained(tokenizer)

/opt/conda/lib/python3.7/site-packages/transformers/tokenization_auto.py in from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs)
    193         config = kwargs.pop("config", None)
    194         if not isinstance(config, PretrainedConfig):
--> 195             config = AutoConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
    196 
    197         if "bert-base-japanese" in pretrained_model_name_or_path:

/opt/conda/lib/python3.7/site-packages/transformers/configuration_auto.py in from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
    194 
    195         """
--> 196         config_dict, _ = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
    197 
    198         if "model_type" in config_dict:

/opt/conda/lib/python3.7/site-packages/transformers/configuration_utils.py in get_config_dict(cls, pretrained_model_name_or_path, **kwargs)
    250                 f"- or '{pretrained_model_name_or_path}' is the correct path to a directory containing a {CONFIG_NAME} file\n\n"
    251             )
--> 252             raise EnvironmentError(msg)
    253 
    254         except json.JSONDecodeError:

OSError: Can't load config for 'distilbert-base-cased'. Make sure that:

- 'distilbert-base-cased' is a correct model identifier listed on 'https://huggingface.co/models'

- or 'distilbert-base-cased' is the correct path to a directory containing a config.json file
```
Hello! Do you have internet access in the environment where your script is run? Can you do the following:

```py
from transformers import DistilBertModel

model = DistilBertModel.from_pretrained("distilbert-base-cased")
```
?<|||||>Sorry my bad.
Internet was off.
It is working fine.
Thank you.