model google/muril-base-cased has effectively infinite model_max_length
### System Info

```shell
>>> transformers.__version__
'4.18.0'
>>> tokenizers.__version__
'0.12.1'
```


### Who can help?

@LysandreJik
@SaulLu


### Information

- [ ] The official example scripts
- [X] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)

### Reproduction

The muril-base-cased model has the model_max_length filled out incorrectly.  For example:

```
>>> from transformers import AutoTokenizer
>>> tokenizer = AutoTokenizer.from_pretrained("google/muril-base-cased")
tokenizer.model_max_length
>>> tokenizer.model_max_length
1000000000000000019884624838656
```




### Expected behavior

I am fairly certain the correct size is 512

Thank you for the issue @AngledLuffa ! It's interesting to know that this is an important feature for you.

Unfortunately we can't do much from `transformers` as `transformers` only retrieves the `model_max_length` key from the [`tokenizer_config.json` file](https://huggingface.co/google/muril-base-cased/blob/main/tokenizer_config.json). When the `model_max_length` key is not filled in, a default "infinite" value is filled in.<|||||>I tried making a topic here:

https://discuss.huggingface.co/t/muril-base-cased-has-infinity-for-model-max-length/17838<|||||>Hi @AngledLuffa,

I think the [new feature](https://huggingface.co/blog/community-update) that has just been deployed on the Hub might solve your problem!

It is now possible to open discussions on a hub model (or even propose a change in the tokenizer configuration!). Would you be interested in trying this out? It should ping the authors and invite them to make the change on the hub!<|||||>Thanks, I'll give that a try<|||||>Closing as the issue seems to be solved thanks to your message on the hub :confetti_ball: 