documentation missing how to split a dataset
this seems to work for my specific problem:

`self.train_ds, self.test_ds, self.val_ds = map(_prepare_ds, ('train', 'test[:25%]+test[50%:75%]', 'test[75%:]'))`
I am trying to understand how to split a dataset ( as arrow_dataset). 
I know I can do something like this to access a split which is already in the original dataset : 

`ds_test = nlp.load_dataset('imdb, split='test') `

But how can I split ds_test into a test and a validation set (without reading the data into memory and keeping the arrow_dataset as container)?
I guess it has something to do with the module split :-) but there is no real documentation in the code but only a reference to a longer description: 

> See the  [guide on splits](https://github.com/huggingface/nlp/tree/master/docs/splits.md)  for more information.

But the guide seems to be missing.

To clarify: I know that this has been modelled after the dataset of tensorflow and that some of the documentation there can be used [like this one](https://www.tensorflow.org/datasets/splits). But to come back to the example above: I cannot simply split the testset doing this: 
`ds_test = nlp.load_dataset('imdb, split='test'[:5000]) `
`ds_val = nlp.load_dataset('imdb, split='test'[5000:])`

because the imdb test data is sorted by class (probably not a good idea anyway)

documentation missing how to split a dataset 
 I am trying to understand how to split a dataset ( as arrow_dataset). 
I know I can do something like this to access a split which is already in the original dataset : 

`ds_test = nlp.load_dataset('imdb, split='test') `

But how can I split ds_test into a test and a validation set (without reading the data into memory and keeping the arrow_dataset as container)?
I guess it has something to do with the module split :-) but there is no real documentation in the code but only a reference to a longer description: 

> See the  [guide on splits](https://github.com/huggingface/nlp/tree/master/docs/splits.md)  for more information.

But the guide seems to be missing.

To clarify: I know that this has been modelled after the dataset of tensorflow and that some of the documentation there can be used [like this one](https://www.tensorflow.org/datasets/splits). But to come back to the example above: I cannot simply split the testset doing this: 
`ds_test = nlp.load_dataset('imdb, split='test'[:5000]) `
`ds_val = nlp.load_dataset('imdb, split='test'[5000:])`

because the imdb test data is sorted by class (probably not a good idea anyway)
 
 this seems to work for my specific problem:

`self.train_ds, self.test_ds, self.val_ds = map(_prepare_ds, ('train', 'test[:25%]+test[50%:75%]', 'test[75%:]'))`