Toxicity fails with datasets 4.0.0
Hi ! You can fix this by upgrading `evaluate`:

```
pip install -U evaluate
``` Thanks, verified evaluate 0.4.5 works!
### Describe the bug

With the latest 4.0.0 release, huggingface toxicity evaluation module fails with error: `ValueError: text input must be of type `str` (single example), `List[str]` (batch or single pretokenized example) or `List[List[str]]` (batch of pretokenized examples).`

### Steps to reproduce the bug

Repro:
```
>>> toxicity.compute(predictions=["This is a response"])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/serena.ruan/miniconda3/envs/mlflow-310/lib/python3.10/site-packages/evaluate/module.py", line 467, in compute
    output = self._compute(**inputs, **compute_kwargs)
  File "/Users/serena.ruan/.cache/huggingface/modules/evaluate_modules/metrics/evaluate-measurement--toxicity/2390290fa0bf6d78480143547c6b08f3d4f8805b249df8c7a8e80d0ce8e3778b/toxicity.py", line 135, in _compute
    scores = toxicity(predictions, self.toxic_classifier, toxic_label)
  File "/Users/serena.ruan/.cache/huggingface/modules/evaluate_modules/metrics/evaluate-measurement--toxicity/2390290fa0bf6d78480143547c6b08f3d4f8805b249df8c7a8e80d0ce8e3778b/toxicity.py", line 103, in toxicity
    for pred_toxic in toxic_classifier(preds):
  File "/Users/serena.ruan/miniconda3/envs/mlflow-310/lib/python3.10/site-packages/transformers/pipelines/text_classification.py", line 159, in __call__
    result = super().__call__(*inputs, **kwargs)
  File "/Users/serena.ruan/miniconda3/envs/mlflow-310/lib/python3.10/site-packages/transformers/pipelines/base.py", line 1431, in __call__
    return self.run_single(inputs, preprocess_params, forward_params, postprocess_params)
  File "/Users/serena.ruan/miniconda3/envs/mlflow-310/lib/python3.10/site-packages/transformers/pipelines/base.py", line 1437, in run_single
    model_inputs = self.preprocess(inputs, **preprocess_params)
  File "/Users/serena.ruan/miniconda3/envs/mlflow-310/lib/python3.10/site-packages/transformers/pipelines/text_classification.py", line 183, in preprocess
    return self.tokenizer(inputs, return_tensors=return_tensors, **tokenizer_kwargs)
  File "/Users/serena.ruan/miniconda3/envs/mlflow-310/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2867, in __call__
    encodings = self._call_one(text=text, text_pair=text_pair, **all_kwargs)
  File "/Users/serena.ruan/miniconda3/envs/mlflow-310/lib/python3.10/site-packages/transformers/tokenization_utils_base.py", line 2927, in _call_one
    raise ValueError(
ValueError: text input must be of type `str` (single example), `List[str]` (batch or single pretokenized example) or `List[List[str]]` (batch of pretokenized examples).
```

### Expected behavior

This works before 4.0.0 release

### Environment info

- `datasets` version: 4.0.0
- Platform: macOS-15.5-arm64-arm-64bit
- Python version: 3.10.16
- `huggingface_hub` version: 0.33.0
- PyArrow version: 19.0.1
- Pandas version: 2.2.3
- `fsspec` version: 2024.12.0