error when loading dataset in Hugging Face: NoneType error is not callable
Hi ! I couldn't reproduce on my side, can you try deleting your cache at `~/.cache/huggingface/modules/datasets_modules/datasets/InstaDeepAI--nucleotide_transformer_downstream_tasks_revised` and try again ? For some reason `datasets` wasn't able to find the DatasetBuilder class in the python script of this dataset I've met the same problem when importing [LongBench-v1](https://github.com/THUDM/LongBench/blob/main/LongBench/README.md). the debugger reports `dataset_module.builder_configs_parameters.builder_configs` as `None` so that no `builder_cls` gets created:

<img width="711" alt="Image" src="https://github.com/user-attachments/assets/b62bdea7-442b-47dc-b892-87f4d235e324" />

does this mean that I need to downgrade `datasets`? I tried downgrading `datasets` to v2.20.0 and it works fine now...

I think there might be some compatibility issues during code updates between `v2.20.0` and `v3.0.0` 🤔 

also I suggest @nanu23333 to see if downgrading works. Found the same problem. When I tried to downgrade the datasets to version below v3.0.0, another problem was raised:  `UnicodeDecodeError: 'utf-8' codec can't decode byte 0xb5 in position 1: invalid start byte` 
when I use the pip install datasets==3.3, I come across the error。Then I 
```
pip uninstall datasets
pip install datasets==2.21.0
```
It is OK now
### Describe the bug

I met an error when running a notebook provide by Hugging Face,  and met the error.

```
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[2], line 5
      3 # Load the enhancers dataset from the InstaDeep Hugging Face ressources
      4 dataset_name = "enhancers_types"
----> 5 train_dataset_enhancers = load_dataset(
      6         "InstaDeepAI/nucleotide_transformer_downstream_tasks_revised",
      7         dataset_name,
      8         split="train",
      9         streaming= False,
     10     )
     11 test_dataset_enhancers = load_dataset(
     12         "InstaDeepAI/nucleotide_transformer_downstream_tasks_revised",
     13         dataset_name,
     14         split="test",
     15         streaming= False,
     16     )

File /public/home/hhl/miniconda3/envs/transformer/lib/python3.9/site-packages/datasets/load.py:2129, 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, trust_remote_code, **config_kwargs)
   2124 verification_mode = VerificationMode(
   2125     (verification_mode or VerificationMode.BASIC_CHECKS) if not save_infos else VerificationMode.ALL_CHECKS
   2126 )
   2128 # Create a dataset builder
-> 2129 builder_instance = load_dataset_builder(
   2130     path=path,
   2131     name=name,
   2132     data_dir=data_dir,
   2133     data_files=data_files,
   2134     cache_dir=cache_dir,
   2135     features=features,
   2136     download_config=download_config,
   2137     download_mode=download_mode,
   2138     revision=revision,
   2139     token=token,
   2140     storage_options=storage_options,
   2141     trust_remote_code=trust_remote_code,
   2142     _require_default_config_name=name is None,
   2143     **config_kwargs,
   2144 )
   2146 # Return iterable dataset in case of streaming
   2147 if streaming:

File /public/home/hhl/miniconda3/envs/transformer/lib/python3.9/site-packages/datasets/load.py:1886, in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, token, storage_options, trust_remote_code, _require_default_config_name, **config_kwargs)
   1884 builder_cls = get_dataset_builder_class(dataset_module, dataset_name=dataset_name)
   1885 # Instantiate the dataset builder
-> 1886 builder_instance: DatasetBuilder = builder_cls(
   1887     cache_dir=cache_dir,
   1888     dataset_name=dataset_name,
   1889     config_name=config_name,
   1890     data_dir=data_dir,
   1891     data_files=data_files,
   1892     hash=dataset_module.hash,
   1893     info=info,
   1894     features=features,
   1895     token=token,
   1896     storage_options=storage_options,
   1897     **builder_kwargs,
   1898     **config_kwargs,
   1899 )
   1900 builder_instance._use_legacy_cache_dir_if_possible(dataset_module)
   1902 return builder_instance

TypeError: 'NoneType' object is not callable
```

I have checked my internet, it worked well. And the dataset name was just copied from the Hugging Face. 
Totally no idea what is wrong! 

### Steps to reproduce the bug

To reproduce the bug you may run

```
from datasets import load_dataset, Dataset

# Load the enhancers dataset from the InstaDeep Hugging Face ressources
dataset_name = "enhancers_types"
train_dataset_enhancers = load_dataset(
        "InstaDeepAI/nucleotide_transformer_downstream_tasks_revised",
        dataset_name,
        split="train",
        streaming= False,
    )
test_dataset_enhancers = load_dataset(
        "InstaDeepAI/nucleotide_transformer_downstream_tasks_revised",
        dataset_name,
        split="test",
        streaming= False,
    )
```

### Expected behavior

1. what may be the reasons of the error
2. how can I fine which reason lead to the error
3. how can I save the problem

### Environment info

```
- `datasets` version: 3.2.0
- Platform: Linux-5.15.0-117-generic-x86_64-with-glibc2.31
- Python version: 3.9.21
- `huggingface_hub` version: 0.27.0
- PyArrow version: 18.1.0
- Pandas version: 2.2.3
- `fsspec` version: 2024.9.0
```