Add British Library books dataset
Thanks for all the help and suggestions

> Since the dataset has a very specific structure it might not be that easy so feel free to ping me if you have questions or if I can help !

I did get a little stuck here! So far I have created directories for each config i.e:

`datasets/datasets/blbooks/dummy/1700_1799/1.0.2/dummy_data.zip` 

I have then added two examples of the `jsonl.gz` files that are in the underlying dataset to each dummy_data directory.This fails the test using local files. 

Since 

```python
def _generate_examples(self, data_dirs):
```

takes as input `data_dirs` which is a list of `iter_dirs` do I need to put the dummy files inside another directory? i.e. 

`datasets/datasets/blbooks/dummy/1700_1799/1.0.2/dummy_data/1700/00.jsonl.gz` 


 
This pull request adds a dataset of text from digitised (primarily 19th Century) books from the British Library. This collection has previously been used for training language models, e.g. https://github.com/dbmdz/clef-hipe/blob/main/hlms.md. It would be nice to make this dataset more accessible for others to use through datasets. 

This is still a WIP but I wanted to get some initial feedback in particular; I wanted to check:
- I am handling the use of `iter_archive` correctly - I intend to ensure that `dl_manager.download` gets the complete list of URLs to download upfront, so the progress bar knows how much is left to download and then to pass through the `gen_kwargs` a list of downloaded zip archives wrapped in `iter_archive`. I am unsure if there is a more elegant approach for this?
- the number of configs: I have aimed to keep this limited - there are a lot of URLs covering the entire dataset, but I have tried to base the configs on what I believe the majority of people will want to they are not presented with too many options - I am happy to hear suggestions for changing this

If there are other glaring omissions or mistakes, I'd be happy to hear them. If this approach seems sensible in general, I will finish all the remaining TODOs, generate dummy_data, etc. 
 