Add configurable options to `seqeval` metric
Hi @marrodion. 

Thanks for pointing this out. It would be great to incorporate this metric-specific enhancement.

Another possibility would be to require the user to input the scheme as a string `mode="strict", scheme="IOB2"` and then dynamically import the corresponding module using Python `importlib`:
```python
if scheme:
    scheme = importlib.import_module(f"seqeval.scheme.{scheme}")
```

Feel free to create a Pull Request to make this contribution.
Right now `load_metric("seqeval")` only works in the default mode of evaluation (equivalent to conll evaluation).

However, seqeval library [supports](https://github.com/chakki-works/seqeval#support-features) different evaluation schemes (IOB1, IOB2, etc.), which can be plugged in just by supporting additional kwargs in `Seqeval._compute`
https://github.com/huggingface/datasets/blob/85cf7ff920c90ca2e12bedca12b36d2a043c3da2/metrics/seqeval/seqeval.py#L109

Things that would be relevant are, for example, supporting `mode="strict", scheme=IOB2` to count only full entity match as a true positive and omit partial matches.

The only problem I see is that the spirit of `metrics` seems to not require additional imports from user. `seqeval` only supports schemes as objects, without any string aliases. 

It can be solved naively with mapping like `{"IOB2": seqeval.scheme.IOB2}`. Or just left as is and require user to explicitly import scheme from `seqeval` if he wants to configure it past the default implementation.

If that makes sense, I am happy to implement the change.