Bug?/Question? Vocab of RoBERTa different from GPT2
Author: KaiserWhoLearns
Pull request: no

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
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- `transformers` version: 4.5.1
- Platform: Linux-5.11.0-34-generic-x86_64-with-debian-bullseye-sid
- Python version: 3.7.11
- PyTorch version (GPU?): 1.9.1+cu111 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No

### Who can help
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Models:

- GPT-2, GPT: @patrickvonplaten, @LysandreJik

If the model isn't in the list, ping @LysandreJik who will redirect you to the correct contributor.

Library:
- Tokenizers: @LysandreJik

Model hub:

- for issues with a model, report at https://discuss.huggingface.co/ and tag the model's creator.

## Information

Model I am using (Bert, XLNet ...):

The problem arises when using:
* [ (Pdb) RobertaTokenizer.from_pretrained('roberta-large').vocab_size
50265
(Pdb) GPT2Tokenizer.from_pretrained('gpt2').vocab_size
50257] 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.
2.
3.

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- GPT-2, GPT: @patrickvonplaten, @LysandreJik
- If the model isn't in the list, ping @LysandreJik who will redirect you to the correct contributor. (Not sure who I should ping for RoBERTa)

Library:
- Tokenizers: @LysandreJik

## Problem

Model I am using: GPT-2, RoBERTa

The problem arises when I ran:
```
RobertaTokenizer.from_pretrained('roberta-large').vocab_size
Output: 50265
GPT2Tokenizer.from_pretrained('gpt2').vocab_size
Output: 50257
```

## Expected behavior
Since RoBERTa and GPT-2 share vocabulary, are they supposed to have equal `vocab_size`? Not sure if this is a question or bug, so I put it here. If this is intended, may I ask where the difference comes from?
<!-- A clear and concise description of what you would expect to happen. -->


Comments:
Hi there!
GPT-2 and RoBERTa both use byte-level Byte-Pair-Encoding for tokenization but they are different tokenizers, trained on different datasets with different `vocab_size`. So this is not a bug. They share the tokenization method but are essentially different tokenizers. 

Also, please use the [forum](https://discuss.huggingface.co/) for such questions. Thank you :) 

> Hi there! GPT-2 and RoBERTa both use byte-level Byte-Pair-Encoding for tokenization but they are different tokenizers, trained on different datasets with different `vocab_size`. So this is not a bug. They share the tokenization method but are essentially different tokenizers.
> 
> Also, please use the [forum](https://discuss.huggingface.co/) for such questions. Thank you :)

I see, thank you very much! I am confused a bit because of seeing paper like these (https://aclanthology.org/2020.tacl-1.18.pdf, https://aclanthology.org/2020.emnlp-main.344.pdf) using GPT2 and RoBERTa since they share the vocab..