IterableDataset with_format does not support 'device' keyword for jax
### Describe the bug

As seen here: https://huggingface.co/docs/datasets/use_with_jax dataset.with_format() supports the keyword 'device', to put data on a specific device when loaded as jax. However, when called on an IterableDataset, I got the error `TypeError: with_format() got an unexpected keyword argument 'device'`

Looking over the code, it seems IterableDataset support only pytorch and no support for jax device keyword? 
https://github.com/huggingface/datasets/blob/fc5c84f36684343bff3e424cb0fd1ac5ecdd66da/src/datasets/iterable_dataset.py#L1029



### Steps to reproduce the bug

1. Load an IterableDataset (tested in streaming mode)
2. Call with_format('jax',device=device)

### Expected behavior

I expect to call `with_format('jax', device=device)`  as per [documentation](https://huggingface.co/docs/datasets/use_with_jax) without error

### Environment info

Tested with installing newest (dev) and also pip release (2.10.1).
- `datasets` version: 2.10.2.dev0
- Platform: Linux-5.15.89+-x86_64-with-debian-bullseye-sid
- Python version: 3.7.12
- Huggingface_hub version: 0.12.1
- PyArrow version: 11.0.0
- Pandas version: 1.3.5

Hi! Yes, only `torch` is currently supported. Unlike `Dataset`, `IterableDataset` is not PyArrow-backed, so we cannot simply call `to_numpy` on the underlying subtables to format them numerically. Instead, we must manually convert examples to (numeric) arrays while preserving consistency with `Dataset`, which is not trivial, so this is still a to-do. Any plans to support it in the future? Or would streaming dataset be left without support for jax and tensorflow?