Guardian authorship dataset
Hi ! Glad you managed to fix the version issue.

The command `
python nlp-cli dummy_data datasets/guardian_authorship --save_infos --all_configs` is supposed to generate a json file `dataset_infos.json` next to your dataset script, but I can't see it in the PR.
Can you make sure you have the json file on your side and that you have pushed it ? Done! Is there anything else that I should do? and would the new dataset be available via the NLP package now?   Sorry I forgot to merge this one ! Doing it now Thanks for the heads up ;) No worries, this is my first contribution to an online package, and I feel very proud it's part of this library :) Thank you very much!
A new dataset: Guardian news articles for authorship attribution

**tests passed:**
python nlp-cli dummy_data datasets/guardian_authorship --save_infos --all_configs

RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_guardian_authorship

**Tests failed:**
Real data: RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_guardian_authorship
output: __init__() missing 3 required positional arguments: 'train_folder', 'valid_folder', and 'tes...' 

Remarks: This is the init function of my class. I am not sure why it passes in both my tests and with nlp-cli, but fails here. By the way, I ran this command with another 2 datasets and they failed:
* _glue - OSError: Cannot find data file.
*_newsgroup - FileNotFoundError: Local file datasets/newsgroup/dummy/18828_comp.graphics/3.0.0/dummy_data.zip doesn't exist

Thank you for letting us contribute to such a huge and important library! 

EDIT:
I was able to fix the dummy_data issue. This dataset has around 14 configurations. I was testing with only 2, but their versions were not in a sequence, they were V1.0.0 and V.12.0.0. It seems that the testing code generates testes for all the versions from 0 to MAX, and was testing for versions (and dummy_data.zip files) that do not exist. I fixed that by changing the versions to 1 and 2.

