Error in pipeline() when model left as None
## 🐛 Bug

<!-- Important information -->

Model I am using (Bert, XLNet....): Default models as per `SUPPORTED_TASKS` config in [pipeline.py](https://github.com/huggingface/transformers/blob/master/src/transformers/pipelines.py)

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

The problem arise when using:
* [x] the official example scripts: (`pipeline.py`)
* [ ] my own modified scripts: (give details)

The tasks I am working on is:
* [x] an official GLUE/SQUaD task: (`question-answering`, `ner`, `feature-extraction`, `sentiment-analysis`)
* [ ] my own task or dataset: (give details)

## To Reproduce

Steps to reproduce the behavior:

1. Install `transformers` 2.3.0
2. Run [example](https://github.com/huggingface/transformers#quick-tour-of-pipelines)

<!-- If you have a code sample, error messages, stack traces, please provide it here as well. -->

```py
from transformers import pipeline
>>> nlp = pipeline('question-answering')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "D:\Continuum\anaconda3\envs\transformers\lib\site-packages\transformers\pipelines.py", line 860, in pipeline
    model = models[framework]
TypeError: string indices must be integers
>>> nlp = pipeline('question-answering', model='distilbert-base-uncased-distilled-squad', tokenizer='distilbert-base-uncased')
```

## Expected behavior

Leaving `model`/`tokenizer` args to `None` should not yield error.

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

## Environment

* OS: system='Windows', release='10', version='10.0.17134', machine='AMD64'
* Python version: 3.5.5
* PyTorch version: 1.3.1
* PyTorch Transformers version (or branch): 2.3.0
* Using GPU ? No
* Distributed of parallel setup ? No
* Any other relevant information:

## Additional context

<!-- Add any other context about the problem here. -->

Upgraded to Python 3.6.7, and two of _tasks_ (sentiment-analysis and question-answering) works as expected (i.e., no error without specifying `model` args).

The remaining two _tasks_ (ner and feature-extraction) fail on a new (similar) error:

#### feature-extraction
```py
>>> from transformers import pipeline
To use data.metrics please install scikit-learn. See https://scikit-learn.org/stable/index.html
>>> nlp = pipeline('feature-extraction')
Traceback (most recent call last):
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\transformers\modeling_utils.py", line 415, in from_pretrained
    state_dict = torch.load(resolved_archive_file, map_location='cpu')
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\torch\serialization.py", line 426, in load
    return _load(f, map_location, pickle_module, **pickle_load_args)
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\torch\serialization.py", line 620, in _load
    deserialized_objects[key]._set_from_file(f, offset, f_should_read_directly)
RuntimeError: unexpected EOF, expected 9211648 more bytes. The file might be corrupted.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\transformers\pipelines.py", line 905, in pipeline
    model = model_class.from_pretrained(model, config=config, **model_kwargs)
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\transformers\modeling_auto.py", line 238, in from_pretrained
    return DistilBertModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\transformers\modeling_utils.py", line 417, in from_pretrained
    raise OSError("Unable to load weights from pytorch checkpoint file. "
OSError: Unable to load weights from pytorch checkpoint file. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True.
```

#### ner
```py
>>> from transformers import pipeline
To use data.metrics please install scikit-learn. See https://scikit-learn.org/stable/index.html
>>> nlp = pipeline('ner')
Traceback (most recent call last):
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\transformers\modeling_utils.py", line 415, in from_pretrained
    state_dict = torch.load(resolved_archive_file, map_location='cpu')
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\torch\serialization.py", line 426, in load
    return _load(f, map_location, pickle_module, **pickle_load_args)
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\torch\serialization.py", line 620, in _load
    deserialized_objects[key]._set_from_file(f, offset, f_should_read_directly)
RuntimeError: unexpected EOF, expected 3733591 more bytes. The file might be corrupted.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\transformers\pipelines.py", line 905, in pipeline
    model = model_class.from_pretrained(model, config=config, **model_kwargs)
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\transformers\modeling_auto.py", line 882, in from_pretrained
    return BertForTokenClassification.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
  File "D:\Continuum\anaconda3\envs\transformers-py36\lib\site-packages\transformers\modeling_utils.py", line 417, in from_pretrained
    raise OSError("Unable to load weights from pytorch checkpoint file. "
OSError: Unable to load weights from pytorch checkpoint file. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True.
```

#### Troubleshooting attempts
1. Tried specifying `model` args, but Python crashes every time.
2. Tried adding `force_download=True`, but same error as above<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
<|||||>To close the loop.

Using `transformers-2.5.1` solves the issue.

Thanks!