

TITLE
fast tokenizer issue on most user uploaded models

COMMENTS
7

REACTIONS
+1: 0
-1: 0
laugh: 0
hooray: 0
heart: 0
rocket: 0
eyes: 0

BODY
## Environment info

- `transformers` version: 3.4.0
- Platform: Linux-5.8.0-25-generic-x86_64-with-glibc2.32
- Python version: 3.8.6
- PyTorch version (GPU?): 1.6.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: yes

### Who can help
@mfuntowicz @julien-c
 
## Information

Found the bug on `camembert/camembert-base-ccnet` but probably common to many models uploaded by users.
On camembert base model, it works out of the box (there is no bug).

## To reproduce

Since `tokenizer` 0.9, it's possible to load the many unigram based tokenizers with the fast Rust implementation.  
It appears that the file `tokenizer_config.json` of some of them is not up to date, in particular the information `"model_max_length": 512` is missing.

Because of that, the value of `model_max_length` is a very big integer.

```python
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("camembert/camembert-base-ccnet", use_fast=True)
tokenizer.model_max_length
# Out[4]: 1000000000000000019884624838656
```

To fix it, the field model_max_length has to be added to the config file.

## Expected behavior

I would expect `tokenizer.model_max_length` to be equal to 512.
