IterableDataset raises exception instead of retrying

### Describe the bug

In light of the recent server outages, I decided to look into whether I could somehow wrap my IterableDataset streams to retry rather than error out immediately. To my surprise, `datasets` [already supports retries](https://github.com/huggingface/datasets/issues/6172#issuecomment-1794876229). Since a commit by @lhoestq [last week](https://github.com/huggingface/datasets/commit/a188022dc43a76a119d90c03832d51d6e4a94d91), that code lives here:

https://github.com/huggingface/datasets/blob/fe2bea6a4b09b180bd23b88fe96dfd1a11191a4f/src/datasets/utils/file_utils.py#L1097C1-L1111C19

If GitHub code snippets still aren't working, here's a copy:
```python
    def read_with_retries(*args, **kwargs):
        disconnect_err = None
        for retry in range(1, max_retries + 1):
            try:
                out = read(*args, **kwargs)
                break
            except (ClientError, TimeoutError) as err:
                disconnect_err = err
                logger.warning(
                    f"Got disconnected from remote data host. Retrying in {config.STREAMING_READ_RETRY_INTERVAL}sec [{retry}/{max_retries}]"
                )
                time.sleep(config.STREAMING_READ_RETRY_INTERVAL)
        else:
            raise ConnectionError("Server Disconnected") from disconnect_err
        return out
```

With the latest outage, the end of my stack trace looked like this:
```
...
  File "/miniconda3/envs/draft/lib/python3.11/site-packages/datasets/download/streaming_download_manager.py", line 342, in read_with_retries
    out = read(*args, **kwargs)
          ^^^^^^^^^^^^^^^^^^^^^
  File "/miniconda3/envs/draft/lib/python3.11/gzip.py", line 301, in read
    return self._buffer.read(size)
           ^^^^^^^^^^^^^^^^^^^^^^^
  File "/miniconda3/envs/draft/lib/python3.11/_compression.py", line 68, in readinto
    data = self.read(len(byte_view))
           ^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/miniconda3/envs/draft/lib/python3.11/gzip.py", line 505, in read
    buf = self._fp.read(io.DEFAULT_BUFFER_SIZE)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/miniconda3/envs/draft/lib/python3.11/gzip.py", line 88, in read
    return self.file.read(size)
           ^^^^^^^^^^^^^^^^^^^^
  File "/miniconda3/envs/draft/lib/python3.11/site-packages/fsspec/spec.py", line 1856, in read
    out = self.cache._fetch(self.loc, self.loc + length)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/miniconda3/envs/draft/lib/python3.11/site-packages/fsspec/caching.py", line 189, in _fetch
    self.cache = self.fetcher(start, end)  # new block replaces old
                 ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/hf_file_system.py", line 626, in _fetch_range
    hf_raise_for_status(r)
  File "/miniconda3/envs/draft/lib/python3.11/site-packages/huggingface_hub/utils/_errors.py", line 333, in hf_raise_for_status
    raise HfHubHTTPError(str(e), response=response) from e
huggingface_hub.utils._errors.HfHubHTTPError: 504 Server Error: Gateway Time-out for url: https://huggingface.co/datasets/allenai/c4/resolve/1588ec454efa1a09f29cd18ddd04fe05fc8653a2/en/c4-train.00346-of-01024.json.gz
```

Indeed, the code for retries only catches `ClientError`s and `TimeoutError`s, and all other exceptions, *including HuggingFace's own custom HTTP error class*, **are not caught. Nothing is retried,** and instead the exception is propagated upwards immediately.

### Steps to reproduce the bug

Not sure how you reproduce this. Maybe unplug your Ethernet cable while streaming a dataset; the issue is pretty clear from the stack trace.

### Expected behavior

All HTTP errors while iterating a streamable dataset should cause retries.

### Environment info

Output from `datasets-cli env`:
- `datasets` version: 2.18.0
- Platform: Linux-4.18.0-513.24.1.el8_9.x86_64-x86_64-with-glibc2.28
- Python version: 3.11.7
- `huggingface_hub` version: 0.20.3
- PyArrow version: 15.0.0
- Pandas version: 2.2.0
- `fsspec` version: 2023.10.0