Support cloud storage in load_dataset
Or for example an archive on GitHub releases!  Before I added support for JXL (locally only, PR still pending) I was considering hosting my files on GitHub instead...
Would be nice to be able to do
```python
data_files=["s3://..."]
storage_options = {...}
load_dataset(..., data_files=data_files, storage_options=storage_options)
```
or even
```python
load_dataset("gs://...")
```

The idea would be to use `fsspec` as in `download_and_prepare` and `save_to_disk`.

This has been requested several times already. Some users want to use their data from private cloud storage to train models

related:

https://github.com/huggingface/datasets/issues/3490
https://github.com/huggingface/datasets/issues/5244
[forum](https://discuss.huggingface.co/t/how-to-use-s3-path-with-load-dataset-with-streaming-true/25739/2)