Adding pseudo-labels to datasets
Nice ! :)
It's indeed the first time we have such contributions so we'll have to figure out the appropriate way to integrate them.
Could you add details on what they could be used for ?
 They can be used as training data for a smaller model. Sounds just like a regular dataset to me then, no? A new configuration for those datasets should do the job then.
Note that until now datasets like xsum only had one configuration. It means that users didn't have to specify the configuration name when loading the dataset. If we add new configs, users that update the lib will have to update their code to specify the default/standard configuration name (not the one with pseudo labels). Could also be a `user-namespace` dataset maybe? Oh yes why not. I'm more in favor of this actually since pseudo labels are things that users (not dataset authors in general) can compute by themselves and share with the community ![image](https://user-images.githubusercontent.com/6045025/96045248-b528a380-0e3f-11eb-9124-bd55afa031bb.png)

I assume I should (for example) rename the xsum dir, change the URL, and put the modified dir somewhere in S3? You can use the `datasets-cli` to upload the folder with your version of xsum with the pseudo labels.

```
datasets-cli upload_dataset path/to/xsum
```
I recently [uploaded pseudo-labels](https://github.com/huggingface/transformers/blob/master/examples/seq2seq/precomputed_pseudo_labels.md) for CNN/DM, XSUM and WMT16-en-ro to s3, and thom mentioned I should add them to this repo.
Since pseudo-labels are just a large model's generations on an existing dataset, what is the right way to structure this contribution.
I read https://huggingface.co/docs/datasets/add_dataset.html, but it doesn't really cover this type of contribution.

I could, for example, make a new directory, `xsum_bart_pseudolabels` for each set of pseudolabels or add some sort of parametrization to `xsum.py`: https://github.com/huggingface/datasets/blob/5f4c6e830f603830117877b8990a0e65a2386aa6/datasets/xsum/xsum.py

What do you think @lhoestq ?


