google/reformer-enwik8 tokenizer was not found in tokenizers model name list
# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): Reformer

Language I am using the model on (English, Chinese ...): English

The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)

The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. Enter https://huggingface.co/google/reformer-enwik8
2. Look at "Hosted inference API"

The model's tokenizer cannot be found; I'm getting the same error in scripts as the one displayed on your webpage:

```⚠️ This model could not be loaded by the inference API. ⚠️
Error loading tokenizer Model name 'google/reformer-enwik8' was not found in tokenizers model name list (google/reformer-crime-and-punishment). We assumed 'google/reformer-enwik8' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url. OSError("Model name 'google/reformer-enwik8' was not found in tokenizers model name list (google/reformer-crime-and-punishment). We assumed 'google/reformer-enwik8' was a path, a model identifier, or url to a directory containing vocabulary files named ['spiece.model'] but couldn't find such vocabulary files at this path or url.")
```

## Expected behavior

Tokenizer loaded without issues

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: latest
- Platform: your own
- Python version: ?
- PyTorch version (GPU?): ?
- Tensorflow version (GPU?): ?
- Using GPU in script?: ?
- Using distributed or parallel set-up in script?: ?

That's because only the crime and punishment modell has an uploaded tokenizer.
<|||||>`google/reformer-enwik8` is the only model that is a char language model and does not need a tokenizer. If you take a look here: https://huggingface.co/google/reformer-enwik8#reformer-language-model-on-character-level-and-trained-on-enwik8 , you can see that the model does not need a tokenier but a simple python encode and decode function. 

@julien-c @mfuntowicz  - how do you think we can include char lms to `pipelines`? Should we maybe introduce a `is_char_lm` config variable? Or just wrap a dummy tokenizer around the python encode and decode functions?<|||||>Add a `tokenizer_class` optional attribute to config.json which overrides the type of Tokenizer that's instantiated when calling `.from_pretrained()`?<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
