Dataset Viewer issue for alkzar90/NIH-Chest-X-ray-dataset
### Link

https://huggingface.co/datasets/alkzar90/NIH-Chest-X-ray-dataset/viewer/image-classification/train

### Description

See the discussion https://discuss.huggingface.co/t/large-image-dataset-feedback-and-advice-data-viewer-task-template-and-more

For the `train` split, the dataset viewer mentions "no rows". It's incorrect: the issue, in that case, is that the train split cannot be loaded, but no error is raised.

More specifically, the first-rows worker tries to load the rows using the streaming mode, then if it does not work and if the split weights less than 100MB, it tries to load them using the normal mode (downloading all the data). In this case, the split weights more than 100MB, and the streaming mode fails, but does not error for some reason:

```python
>>> ds = load_dataset(path="alkzar90/NIH-Chest-X-ray-dataset", name="image-classification", split="train", streaming=True)
>>> next(iter(ds)) # <- fails, but it's not what is used in the code
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>> import itertools
>>> list(itertools.islice(ds, 101)) # <- this is used in the code and does not raise
[]
```

Note that the normal mode works (but downloads GBs of data):

```python
>>> ds = load_dataset(path="alkzar90/NIH-Chest-X-ray-dataset", name="image-classification", split="train")
Downloading and preparing dataset nih-chest-x-ray-dataset/image-classification to /home/slesage/.cache/huggingface/datasets/alkzar90___nih-chest-x-ray-dataset/image-classification/1.0.0/e6f0b4e0a72a9fad5e268364fb11802e767c4565fb82a19d8283db4323ddf7b2...
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 3.99G/3.99G [01:46<00:00, 37.4MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.02G/4.02G [01:25<00:00, 47.0MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.02G/4.02G [01:21<00:00, 49.3MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.11G/4.11G [01:31<00:00, 44.9MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.18G/4.18G [01:22<00:00, 50.6MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.19G/4.19G [01:25<00:00, 48.8MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 2.91G/2.91G [00:52<00:00, 55.7MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████| 12/12 [09:58<00:00, 49.84s/it]
Extracting data files: 100%|████████████████████████████████████████████████████████████████████████████| 12/12 [05:42<00:00, 28.58s/it]
Extracting data files: 100%|████████████████████████████████████Dataset nih-chest-x-ray-dataset downloaded and prepared to /home/slesage/.cache/huggingface/datasets/alkzar90___nih-chest-x-ray-dataset/image-classification/1.0.0/e6f0b4e0a72a9fad5e268364fb11802e767c4565fb82a19d8283db4323ddf7b2. Subsequent calls will reuse this data.
>>> ds
Dataset({
    features: ['image', 'labels'],
    num_rows: 86524
})
>>> ds[0]
{'image': <PIL.PngImagePlugin.PngImageFile image mode=L size=1024x1024 at 0x7FBEC81F0CA0>, 'labels': [0]}
```

cc @alcazar90 @julien-c

Happy to get help from the @huggingface/datasets team to help fix the streaming issue
Dataset Viewer issue for alkzar90/NIH-Chest-X-ray-dataset: ### Link

https://huggingface.co/datasets/alkzar90/NIH-Chest-X-ray-dataset/viewer/image-classification/train

### Description

See the discussion https://discuss.huggingface.co/t/large-image-dataset-feedback-and-advice-data-viewer-task-template-and-more

For the `train` split, the dataset viewer mentions "no rows". It's incorrect: the issue, in that case, is that the train split cannot be loaded, but no error is raised.

More specifically, the first-rows worker tries to load the rows using the streaming mode, then if it does not work and if the split weights less than 100MB, it tries to load them using the normal mode (downloading all the data). In this case, the split weights more than 100MB, and the streaming mode fails, but does not error for some reason:

```python
>>> ds = load_dataset(path="alkzar90/NIH-Chest-X-ray-dataset", name="image-classification", split="train", streaming=True)
>>> next(iter(ds)) # <- fails, but it's not what is used in the code
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration
>>> import itertools
>>> list(itertools.islice(ds, 101)) # <- this is used in the code and does not raise
[]
```

Note that the normal mode works (but downloads GBs of data):

```python
>>> ds = load_dataset(path="alkzar90/NIH-Chest-X-ray-dataset", name="image-classification", split="train")
Downloading and preparing dataset nih-chest-x-ray-dataset/image-classification to /home/slesage/.cache/huggingface/datasets/alkzar90___nih-chest-x-ray-dataset/image-classification/1.0.0/e6f0b4e0a72a9fad5e268364fb11802e767c4565fb82a19d8283db4323ddf7b2...
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 3.99G/3.99G [01:46<00:00, 37.4MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.02G/4.02G [01:25<00:00, 47.0MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.02G/4.02G [01:21<00:00, 49.3MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.11G/4.11G [01:31<00:00, 44.9MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.18G/4.18G [01:22<00:00, 50.6MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 4.19G/4.19G [01:25<00:00, 48.8MB/s]
Downloading data: 100%|████████████████████████████████████████████████████████████████████████████| 2.91G/2.91G [00:52<00:00, 55.7MB/s]
Downloading data files: 100%|███████████████████████████████████████████████████████████████████████████| 12/12 [09:58<00:00, 49.84s/it]
Extracting data files: 100%|████████████████████████████████████████████████████████████████████████████| 12/12 [05:42<00:00, 28.58s/it]
Extracting data files: 100%|████████████████████████████████████Dataset nih-chest-x-ray-dataset downloaded and prepared to /home/slesage/.cache/huggingface/datasets/alkzar90___nih-chest-x-ray-dataset/image-classification/1.0.0/e6f0b4e0a72a9fad5e268364fb11802e767c4565fb82a19d8283db4323ddf7b2. Subsequent calls will reuse this data.
>>> ds
Dataset({
    features: ['image', 'labels'],
    num_rows: 86524
})
>>> ds[0]
{'image': <PIL.PngImagePlugin.PngImageFile image mode=L size=1024x1024 at 0x7FBEC81F0CA0>, 'labels': [0]}
```

cc @alcazar90 @julien-c

Happy to get help from the @huggingface/datasets team to help fix the streaming issue