Token classification example (run_ner.py) should work without fast tokenizers
# 🚀 Feature request

The token classification example ( [run_ner.py](https://github.com/huggingface/transformers/blob/master/examples/token-classification/run_ner.py) ) calls the Tokenizer with `return_offsets_mapping=True` (line 279).

This is not allowed for Python tokenizers and raises the error `NotImplementedError: return_offset_mapping is not available when using Python tokenizers. To use this feature, change your tokenizer to one deriving from transformers.PreTrainedTokenizerFast.`

run_ner.py should align tokens and labels even if a fast tokenizer is not available.

## Motivation

There isn't a fast tokenizer available for `vinai/bertweet-base`, and I guess this may apply to a few other models as well.  
Passing  `vinai/bertweet-base` as `model_name_or_path` to `run_ner.py` instantly raises `NotImplementedError`.
Yes, this script only supports models that have a fast tokenizer (there is now a clear assert of that after the tokenizer is loaded). The old script will work with models that only have a slow tokenizer.<|||||>> Yes, this script only supports models that have a fast tokenizer (there is no a clear assert of that after the tokenizer is loaded). The old script will work with models that only have a slow tokenizer.

Somebody wrote an assert four days ago. There are certain inconveniences to the old script, e.g. it doesn't utilize the `datasets` library. <|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.<|||||>I am facing same problem in BioGPT
