Dependency errors when trying to use gpt2 using pytorch hub.
Author: VictorAlbertos
Pull request: no

It started today, yesterday it was working fine. When I try to download `gpt2` model from pytorch hub repository, as follows: 

```python
torch.hub.load('huggingface/pytorch-pretrained-BERT', 'gpt2Tokenizer', 'gpt2') 
```

I get the following error: `ModuleNotFoundError: No module named 'sacremoses'`. If I add that dependency manually then I get another error: `ModuleNotFoundError: No module named 'sentencepiece'`. Then I add `sentencepiece` dependency manually just to get another error: `RuntimeError: Cannot find callable gpt2Tokenizer in hubconf`. And this error seems to be related to API changes. 

I'm using a Google Colab GPU instance.

If this is not the right place to post this issue, please re-direct me to the proper source to post the issue. Thanks.

Comments:
I found that https://github.com/huggingface/pytorch-transformers/commit/256086bc6908448fc6aff9b1e19d95c4f6019bee is the source of the issue. Reading the changes I could guess that the new way for retrieving the tokenizer and model is as follows:

```python
tokenizer = torch.hub.load('huggingface/pytorch-transformers', 'tokenizer', 'gpt2')
model = torch.hub.load('huggingface/pytorch-transformers', 'modelWithLMHead', 'gpt2')
```

But I'm not sure if there is an issue with the docs in hub as they seem to not be updated. 

Yes, we are in the process of updating the hub

I'm reopening this issue because I'm getting the next error when trying to import the tokenizer:
`ImportError: cannot import name 'add_start_docstrings'`

<img width="1046" alt="Screenshot 2019-09-06 at 20 15 36" src="https://user-images.githubusercontent.com/2614726/64450882-4da01080-d0e3-11e9-94d0-10a0e57c0e80.png">

 

We can only help you if we have more information on the version/release you
are using.

On Fri, 6 Sep 2019 at 21:17, Víctor Albertos <notifications@github.com>
wrote:

> Reopened #1165
> <https://github.com/huggingface/pytorch-transformers/issues/1165>.
>
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I'm using the version from the hub, you don't specify a version there, as far as I know. 

It's the version of the master branch by default.

I fixed the bug with ee027c8.

Note that you can [specify a specific release](https://pytorch.org/docs/stable/hub.html#torch.hub.load) with torch hub, e.g. use release `1.2.0` with `torch.hub('huggingface/pytorch-transformers:1.2.0', 'model', 'bert-base-uncased')`.

That's what I would advise as it allows you to have clean versioning of your code (you will be sure, in 3 months from now, of the exact version of the model you were using to get your results).

Thanks for fixing the bug so quickly and for the additional information I was not aware of the versioning feature.