How to load existing downloaded dataset ?
Feel free to use `dataset.save_to_disk(...)`, then scp the directory containing the saved dataset and reload it on your other machine using `dataset = load_from_disk(...)`
Hi @mariosasko @lhoestq  @katielink 

Thanks for your contribution and hard work.

### Feature request

First, I download a dataset as normal by:
```
from datasets import load_dataset

dataset = load_dataset('username/data_name', cache_dir='data')
```

The dataset format in `data` directory will be:
```
-data
  |-data_name
    |-test-00000-of-00001-bf4c733542e35fcb.parquet
    |-train-00000-of-00001-2a1df75c6bce91ab.parquet
```


Then I use SCP to clone this dataset into another machine, and then try:
```
from datasets import load_dataset

dataset = load_dataset('data/data_name')  # load from local path
```

This leads to re-generating training and validation split for each time, and the disk quota will be duplicated occupation.

How can I just load the dataset without generating and saving these splits again?

### Motivation

I do not want to download the same dataset in two machines, scp is much faster and better than HuggingFace API. I hope we can directly load the downloaded datasets (.parquest)

### Your contribution

Please refer to the feature