Raise error if `stride` is too high in `TokenClassificationPipeline`
# What does this PR do?

Users were previously not given a warning if they initialized a `TokenClassificationPipeline` with too high a value for `stride` (`stride` is the value that determines how many tokens overlap between chunks if the user choose to split text into chunks).

Unfortunately, it's also possible for a `stride` to be too high if the tokenizer happens to introduce special tokens (e.g. `bert-base-cased` has a maximum length of `512`, but each window gets `2` special tokens, so the highest valid `stride` is `509`) , but there's apparently no easy way to check this in advance (i.e. before the tokenizer is run as part of the pipeline). I think it might be worth fixing the error message ("`pyo3_runtime.PanicException: assertion failed: stride < max_len`") when a tokenizer is called with too high a value of `stride`, to clarify to users that added special tokens subtract from the effective window size.

I also thought it was worth clarifying slightly the function of the `stride` parameter. The way `stride` works in the context of Huggingface tokenizers is almost the opposite of the way it works in many [other contexts](https://www.kaggle.com/code/ryanholbrook/the-sliding-window/tutorial).

Mostly fixes #22789.


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      Pull Request section?
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- [ ] Did you write any new necessary tests?


## Who should review?

@Narsil 

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