Dataset scripts are no longer supported, but found superb.py
I got a pretty similar issue when I try to load bigbio/neurotrial_ner dataset. 
`Dataset scripts are no longer supported, but found neurotrial_ner.py` Same here. I was running this tutorial and got a similar error: https://github.com/openai/whisper/discussions/654 (I'm a first-time transformers library user)

RuntimeError: Dataset scripts are no longer supported, but found librispeech_asr.py

What am I supposed to do at this point?

Thanks hey I got the same error and I have tried to downgrade version to 3.6.0 and it works.
`pip install datasets==3.6.0` Thank you very much @Tin-viAct . That indeed did the trick for me :) 
Now the code continue its normal flow  Thanks @Tin-viAct, Works! I converted [openslr/librispeech_asr](https://huggingface.co/datasets/openslr/librispeech_asr) to Parquet - thanks for reporting.

It's now compatible with `datasets` 4.0  !

I'll try to ping the authors of the other datasets like [s3prl/superb](https://huggingface.co/datasets/s3prl/superb) and [espnet/yodas2](https://huggingface.co/datasets/espnet/yodas2) How come a breaking change was allowed and now requires extra work from individual authors for things to be usable? 

https://en.wikipedia.org/wiki/Backward_compatibility We follow semantic versioning so that breaking changes only occur in major releases. Also note that dataset scripts have been legacy for some time now, with a message on the dataset pages to ask authors to update their datasets.

It's ok to ping older versions of `datasets`, but imo a few remaining datasets need to be converted since they are valuable to the community. I was facing the same issue with a not so familiar dataset in hugging hub . downgrading the datasets version worked ❤️. Thank you @Tin-viAct . Thank you so much, @Tin-viAct ! I’ve been struggling with this issue for about 3 hours, and your suggestion to downgrade datasets worked perfectly. I really appreciate the help—you saved me! > hey I got the same error and I have tried to downgrade version to 3.6.0 and it works. `pip install datasets==3.6.0`

Thank you so much! I was following the [quickstart](https://huggingface.co/docs/datasets/quickstart) and the very first sample fails. Not a good way to get started.... > hey I got the same error and I have tried to downgrade version to 3.6.0 and it works. `pip install datasets==3.6.0`
thank you! I get it.
 I updated `hotpot_qa` and pinged the PolyAI folks to update the dataset used in the quickstart as well: https://huggingface.co/datasets/PolyAI/minds14/discussions/35
edit: merged !
edit2: quickstart dataset is also fixed ! [LegalBench](https://huggingface.co/datasets/nguha/legalbench) is downloaded 10k times a month and is now broken. Would be great to have this fixed. I opened a PR to convert LegalBench to Parquet and reached out to the author: https://huggingface.co/datasets/nguha/legalbench/discussions/34 Thank you very much @Tin-viAct! I’d been looking everywhere for a fix, and your reply saved me :) Tried downgrading the datasets version. But the problem with this is that it had led to compatibility issues and other breaking changes and more errors on other parts of my code  I opened a few more PRs and reached out to the authors:
- https://huggingface.co/datasets/Skylion007/openwebtext/discussions/22
- https://huggingface.co/datasets/stas/openwebtext-10k/discussions/2

Btw if you want to open a PR to a dataset to convert it to Parquet here is the command:

```
uv run --with "datasets==3.6.0" datasets-cli convert_to_parquet <username/dataset-name> --trust_remote_code
```

(just replace the `<username/dataset-name>` with the dataset repository name)
### Describe the bug

Hello,

I'm trying to follow the [Hugging Face Pipelines tutorial](https://huggingface.co/docs/transformers/main_classes/pipelines) but the tutorial seems to work only on old datasets versions.

I then get the error :

```
--------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
Cell In[65], [line 1](vscode-notebook-cell:?execution_count=65&line=1)
----> [1](vscode-notebook-cell:?execution_count=65&line=1) dataset = datasets.load_dataset("superb", name="asr", split="test")
      3 # KeyDataset (only *pt*) will simply return the item in the dict returned by the dataset item
      4 # as we're not interested in the *target* part of the dataset. For sentence pair use KeyPairDataset
      5 for out in tqdm(pipe(KeyDataset(dataset, "file"))):

File ~/Desktop/debug/llm_course/.venv/lib/python3.11/site-packages/datasets/load.py:1392, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, keep_in_memory, save_infos, revision, token, streaming, num_proc, storage_options, **config_kwargs)
   1387 verification_mode = VerificationMode(
   1388     (verification_mode or VerificationMode.BASIC_CHECKS) if not save_infos else VerificationMode.ALL_CHECKS
   1389 )
   1391 # Create a dataset builder
-> [1392](https://file+.vscode-resource.vscode-cdn.net/home/edwin/Desktop/debug/llm_course/~/Desktop/debug/llm_course/.venv/lib/python3.11/site-packages/datasets/load.py:1392) builder_instance = load_dataset_builder(
   1393     path=path,
   1394     name=name,
   1395     data_dir=data_dir,
   1396     data_files=data_files,
   1397     cache_dir=cache_dir,
   1398     features=features,
   1399     download_config=download_config,
   1400     download_mode=download_mode,
   1401     revision=revision,
   1402     token=token,
   1403     storage_options=storage_options,
   1404     **config_kwargs,
   1405 )
   1407 # Return iterable dataset in case of streaming
   1408 if streaming:

File ~/Desktop/debug/llm_course/.venv/lib/python3.11/site-packages/datasets/load.py:1132, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, token, storage_options, **config_kwargs)
   1130 if features is not None:
   1131     features = _fix_for_backward_compatible_features(features)
-> [1132](https://file+.vscode-resource.vscode-cdn.net/home/edwin/Desktop/debug/llm_course/~/Desktop/debug/llm_course/.venv/lib/python3.11/site-packages/datasets/load.py:1132) dataset_module = dataset_module_factory(
   1133     path,
   1134     revision=revision,
   1135     download_config=download_config,
   1136     download_mode=download_mode,
   1137     data_dir=data_dir,
   1138     data_files=data_files,
   1139     cache_dir=cache_dir,
   1140 )
   1141 # Get dataset builder class
   1142 builder_kwargs = dataset_module.builder_kwargs

File ~/Desktop/debug/llm_course/.venv/lib/python3.11/site-packages/datasets/load.py:1031, in dataset_module_factory(path, revision, download_config, download_mode, data_dir, data_files, cache_dir, **download_kwargs)
   1026             if isinstance(e1, FileNotFoundError):
   1027                 raise FileNotFoundError(
   1028                     f"Couldn't find any data file at {relative_to_absolute_path(path)}. "
   1029                     f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}"
   1030                 ) from None
-> [1031](https://file+.vscode-resource.vscode-cdn.net/home/edwin/Desktop/debug/llm_course/~/Desktop/debug/llm_course/.venv/lib/python3.11/site-packages/datasets/load.py:1031)             raise e1 from None
   1032 else:
   1033     raise FileNotFoundError(f"Couldn't find any data file at {relative_to_absolute_path(path)}.")

File ~/Desktop/debug/llm_course/.venv/lib/python3.11/site-packages/datasets/load.py:989, in dataset_module_factory(path, revision, download_config, download_mode, data_dir, data_files, cache_dir, **download_kwargs)
    981 try:
    982     api.hf_hub_download(
    983         repo_id=path,
    984         filename=filename,
   (...)    987         proxies=download_config.proxies,
    988     )
--> [989](https://file+.vscode-resource.vscode-cdn.net/home/edwin/Desktop/debug/llm_course/~/Desktop/debug/llm_course/.venv/lib/python3.11/site-packages/datasets/load.py:989)     raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
    990 except EntryNotFoundError:
    991     # Use the infos from the parquet export except in some cases:
    992     if data_dir or data_files or (revision and revision != "main"):

RuntimeError: Dataset scripts are no longer supported, but found superb.py
```

NB : I tried to replace "superb" by  "anton-l/superb_demo" but I get a 'torchcodec' importing error. Maybe I misunderstood something.

### Steps to reproduce the bug

```
import datasets
from transformers import pipeline
from transformers.pipelines.pt_utils import KeyDataset
from tqdm.auto import tqdm

pipe = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h", device=0)
dataset = datasets.load_dataset("superb", name="asr", split="test")

# KeyDataset (only *pt*) will simply return the item in the dict returned by the dataset item
# as we're not interested in the *target* part of the dataset. For sentence pair use KeyPairDataset
for out in tqdm(pipe(KeyDataset(dataset, "file"))):
    print(out)
    # {"text": "NUMBER TEN FRESH NELLY IS WAITING ON YOU GOOD NIGHT HUSBAND"}
    # {"text": ....}
    # ....
```

### Expected behavior

Get the tutorial expected results

### Environment info

--- SYSTEM INFO ---
Operating System: Ubuntu 24.10                              
Kernel: Linux 6.11.0-29-generic
Architecture: x86-64

--- PYTHON ---
Python 3.11.13

--- VENV INFO ----
datasets=4.0.0
transformers=4.53
tqdm=4.67.1