Force JSON format regardless of file naming on S3
I have a file on S3 created by Data Version Control, it looks like `s3://dvc/ac/badff5b134382a0f25248f1b45d7b2` but contains a json file. If I run 
```python
dataset = load_dataset(
    "json",
    data_files='s3://dvc/ac/badff5b134382a0f25248f1b45d7b2' 
)
```
It gives me 
```
InvalidSchema: No connection adapters were found for 's3://dvc/ac/badff5b134382a0f25248f1b45d7b2'
```
However, I cannot go ahead and change the names of the s3 file. Is there a way to "force" load a S3 url with certain decoder (JSON, CSV, etc.) regardless of s3 URL naming?
Hi ! Support for URIs like `s3://...` is not implemented yet in `data_files=`. You can use the HTTP URL instead if your data is public in the meantime Hi,
I want to make sure I understand this response. I have a set of files on S3 that are private for security reasons. Because they are not public files  I cannot read those files (many are parquet) into my hf notebooks in Kaggle? That can't be correct, can it?  Hi ! There is a discussion at https://github.com/huggingface/datasets/issues/5281

Using the latest `datasets` 2.11 you can try passing fsspec URLs to private buckets to `data_files` in `load_dataset()`. Though this is still experimental and undocumented, so feedback is welcome. You may not have the best experience though, since anything related to performance and caching hasn't been tested properly yet.