Fork dataset
To be able to generate the Arrow dataset you need to either use our csv or json utilities `load_dataset("json", data_files=my_json_files)` OR write your own custom dataset script (you can find some inspiration from the [squad](https://github.com/huggingface/nlp/blob/master/datasets/squad/squad.py) script for example). Custom dataset scripts can be called locally with `nlp.load_dataset(path_to_my_script_directory)`.

This should help you get what you call "Dataset1".

Then using some dataset transforms like `.map` for example you can get to "DatasetNER" and "DatasetREL".

We have a multi-task learning model training I'm trying to convert to using the Arrow-based nlp dataset. 

We're currently training a custom TensorFlow model but the nlp paradigm should be a bridge for us to be able to use the wealth of pre-trained models in Transformers.

Our preprocessing flow parses raw text and json with Entity and Relations annotations and creates 2 datasets for training a NER and Relations prediction heads.

Is there some good way to "fork" dataset-

EG

1. text + json -> Dataset1
1. Dataset1 -> DatasetNER
1. Dataset1 -> DatasetREL

or 

1. text + json -> Dataset1
1. Dataset1 -> DatasetNER
1. Dataset1 + DatasetNER -> DatasetREL


Fork dataset 
 We have a multi-task learning model training I'm trying to convert to using the Arrow-based nlp dataset. 

We're currently training a custom TensorFlow model but the nlp paradigm should be a bridge for us to be able to use the wealth of pre-trained models in Transformers.

Our preprocessing flow parses raw text and json with Entity and Relations annotations and creates 2 datasets for training a NER and Relations prediction heads.

Is there some good way to "fork" dataset-

EG

1. text + json -> Dataset1
1. Dataset1 -> DatasetNER
1. Dataset1 -> DatasetREL

or 

1. text + json -> Dataset1
1. Dataset1 -> DatasetNER
1. Dataset1 + DatasetNER -> DatasetREL

 
 To be able to generate the Arrow dataset you need to either use our csv or json utilities `load_dataset("json", data_files=my_json_files)` OR write your own custom dataset script (you can find some inspiration from the [squad](https://github.com/huggingface/nlp/blob/master/datasets/squad/squad.py) script for example). Custom dataset scripts can be called locally with `nlp.load_dataset(path_to_my_script_directory)`.

This should help you get what you call "Dataset1".

Then using some dataset transforms like `.map` for example you can get to "DatasetNER" and "DatasetREL".
