Error loading StonyBrookNLP/tellmewhy dataset from hub even though local copy loads correctly

## Describe the bug
I have added a new dataset with the identifier `StonyBrookNLP/tellmewhy` to the hub. When I load the individual files using my local copy using `dataset = datasets.load_dataset("json", data_files="data/train.jsonl")`, it loads the dataset correctly. However, when I try to load it from the hub, I get an error (pasted below). Additionally, `dataset = datasets.load_dataset("json", data_dir="data/")` throws the same error.

## Steps to reproduce the bug
```python
dataset = datasets.load_dataset('StonyBrookNLP/tellmewhy')
```

## Expected results
Successfully load the `StonyBrookNLP/tellmewhy` dataset.

## Actual results
```
Using custom data configuration StonyBrookNLP--tellmewhy-82712924092694ff
Downloading and preparing dataset json/StonyBrookNLP--tellmewhy to /home/yklal95/.cache/huggingface/datasets/StonyBrookNLP___json/StonyBrookNLP--tellmewhy-82712924092694ff/0.0.0/a3e658c4731e59120d44081ac10bf85dc7e1388126b92338344ce9661907f253...
Downloading data files: 100%|██████████████████████████████| 3/3 [00:00<00:00, 957.46it/s]
Extracting data files: 100%|███████████████████████████████| 3/3 [00:00<00:00, 299.14it/s]
Traceback (most recent call last):
  File "/home/yklal95/tmw-generalization/src/load_datasets.py", line 17, in <module>
    main(args)
  File "/home/yklal95/tmw-generalization/src/load_datasets.py", line 11, in main
    dataset = datasets.load_dataset(args.dataset_name)
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/load.py", line 1746, in load_dataset
    builder_instance.download_and_prepare(
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 704, in download_and_prepare
    self._download_and_prepare(
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 793, in _download_and_prepare
    self._prepare_split(split_generator, **prepare_split_kwargs)
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 1277, in _prepare_split
    writer.write_table(table)
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/arrow_writer.py", line 524, in write_table
    pa_table = table_cast(pa_table, self._schema)
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 2005, in table_cast
    return cast_table_to_schema(table, schema)
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1969, in cast_table_to_schema
    arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1969, in <listcomp>
    arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()]
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1681, in wrapper
    return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1681, in <listcomp>
    return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1822, in cast_array_to_feature
    casted_values = _c(array.values, feature.feature)
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1683, in wrapper
    return func(array, *args, **kwargs)
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1853, in cast_array_to_feature
    return array_cast(array, feature(), allow_number_to_str=allow_number_to_str)
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1683, in wrapper
    return func(array, *args, **kwargs)
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/table.py", line 1761, in array_cast
    raise TypeError(f"Couldn't cast array of type {array.type} to {pa_type}")
TypeError: Couldn't cast array of type int64 to null
```

## Environment info
<!-- You can run the command `datasets-cli env` and copy-and-paste its output below. -->
- `datasets` version: 2.4.0
- Platform: Linux-4.15.0-121-generic-x86_64-with-glibc2.27
- Python version: 3.9.13
- PyArrow version: 9.0.0
- Pandas version: 1.5.0


Comments:
I think this is because some columns are mostly empty lists. In particular the train and validation splits only have empty lists for `val_ann`. Therefore the type inference doesn't know which type is inside (or it would have to scan the other splits first before knowing).

You can fix that by specifying the features types explicitly.
Then you can save the feature types inside the dataset repository, so that you won't need to specify the features in subsequent calls:
```python
from datasets import load_dataset, Features, Sequence, Value
from datasets.info import DatasetInfosDict

features = Features({
 'narrative': Value('string'),
 'question': Value('string'),
 'original_sentence_for_question': Value('string'),
 'narrative_lexical_overlap': Value('float64'),
 'is_ques_answerable': Value('string'),
 'answer': Value('string'),
 'is_ques_answerable_annotator': Value('string'),
 'original_narrative_form': Sequence(Value('string')),
 'question_meta': Value('string'),
 'helpful_sentences': Sequence(Value('int64')),
 'human_eval': Value('bool'),
 'val_ann': Sequence(Value('int64')),
 'gram_ann': Sequence(Value('int64'))
})
ds = load_dataset('StonyBrookNLP/tellmewhy', features=features)
DatasetInfosDict({"default": ds["train"].info}).write_to_directory("path/to/local/tellmewhy")
```
and then after pushing the change to the dataset repository on the Hub, `load_dataset("StonyBrookNLP/tellmewhy")` will work directly`

(Note that specifying explicit types will be made easier with https://github.com/huggingface/datasets/pull/4926)

`gram_ann` and `val_ann` are annotations that only exist for part of the test set. I wanted to keep all the columns consistent across all files, so I added them to train and validation as well. I'll check if removing them from those files is still compliant with this repo. Otherwise, I will do as you suggested. Thanks @lhoestq !

@lhoestq I followed the exact steps you described but it seems like I'm getting the same error unfortunately. Any other ideas? Thanks in advance

Hi ! If you move `dataset_infos.json` from `data/` to the root of your dataset repository if should work :)

I tried that and pushed to the [hub](https://huggingface.co/datasets/StonyBrookNLP/tellmewhy/tree/main). Now, there is a new error.
```
  File "/home/yklal95/tellmewhy/src/prepare_data.py", line 67, in main
    dataset = load_dataset('StonyBrookNLP/tellmewhy')
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/load.py", line 1746, in load_dataset
    builder_instance.download_and_prepare(
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 704, in download_and_prepare
    self._download_and_prepare(
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/builder.py", line 775, in _download_and_prepare
    verify_checksums(
  File "/home/yklal95/anaconda3/envs/tmw-generalization/lib/python3.9/site-packages/datasets/utils/info_utils.py", line 33, in verify_checksums
    raise ExpectedMoreDownloadedFiles(str(set(expected_checksums) - set(recorded_checksums)))
datasets.utils.info_utils.ExpectedMoreDownloadedFiles: {'/home/yklal95/tellmewhy/data/test.json', '/home/yklal95/tellmewhy/data/validation.json', '/home/yklal95/tellmewhy/data/train.json'}
```
No changes were made to any of the other files and they are still on the hub. Let me know if you have any ideas @lhoestq Thanks!

Oh I see - the code I gave you returns local paths instead of URLs to store metadata about files to download.
I opened a PR in your repo here to remove this: https://huggingface.co/datasets/StonyBrookNLP/tellmewhy/discussions/1
sorry for the inconvenience !

It works now! Thanks a lot @lhoestq