Exception: You're trying to run a `Unigram` model but you're file was trained with a different algorithm
## Environment info
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     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.2.2
- Platform: Linux-3.10.107-1-tlinux2_kvm_guest-0049-x86_64-with-glibc2.10
- Python version: 3.8.5
- PyTorch version (GPU?): 1.7.1 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: no 
- Using distributed or parallel set-up in script?: no

### Who can help
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Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @jplu

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

HF projects:

- nlp datasets: [different repo](https://github.com/huggingface/nlp)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->

## Information

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

The problem arises when using:
* [1 ] 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. open https://github.com/agemagician/ProtTrans/blob/master/Embedding/PyTorch/Basic/ProtAlbert.ipynb
2. when run the code 'tokenizer = AutoTokenizer.from_pretrained("Rostlab/prot_albert", do_lower_case=False )'
3. report errors as the follow:
Downloading: 100%|█████████████████████████████████████████████████████████████████| 505/505 [00:00<00:00, 516kB/s]
Downloading: 100%|██████████████████████████████████████████████████████████████| 238k/238k [00:03<00:00, 77.0kB/s]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/anaconda3/envs/prottrans/lib/python3.8/site-packages/transformers/models/auto/tokenization_auto.py", line 385, in from_pretrained
    return tokenizer_class_fast.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
  File "/home/anaconda3/envs/prottrans/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1768, in from_pretrained
    return cls._from_pretrained(
  File "/home/anaconda3/envs/prottrans/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1841, in _from_pretrained
    tokenizer = cls(*init_inputs, **init_kwargs)
  File "/home/anaconda3/envs/prottrans/lib/python3.8/site-packages/transformers/models/albert/tokenization_albert_fast.py", line 136, in __init__
    super().__init__(
  File "/home/anaconda3/envs/prottrans/lib/python3.8/site-packages/transformers/tokenization_utils_fast.py", line 89, in __init__
    fast_tokenizer = convert_slow_tokenizer(slow_tokenizer)
  File "/home/anaconda3/envs/prottrans/lib/python3.8/site-packages/transformers/convert_slow_tokenizer.py", line 659, in convert_slow_tokenizer
    return converter_class(transformer_tokenizer).converted()
  File "/home/anaconda3/envs/prottrans/lib/python3.8/site-packages/transformers/convert_slow_tokenizer.py", line 349, in converted
    tokenizer = self.tokenizer(self.proto)
  File "/home/anaconda3/envs/prottrans/lib/python3.8/site-packages/transformers/convert_slow_tokenizer.py", line 335, in tokenizer
    raise Exception(
Exception: You're trying to run a `Unigram` model but you're file was trained with a different algorithm


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## Expected behavior

<!-- A clear and concise description of what you would expect to happen. -->

Use "AlbertTokenizer" rather than "AutoTokenizer", this should solve your issue.
Please, check the updated notebook version.<|||||>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.<|||||>Prot_albert tokenizer is returning none type, what changed?