AttributeError: module 'google.protobuf.descriptor' has no attribute '_internal_create_key'
## Environment info
transformers version: '4.26.1'
Platform: databricks

```
from transformers import pipeline
model_path = "cardiffnlp/twitter-xlm-roberta-base-sentiment"
sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
sentiment_task("T'estimo!")
```

## Who can help
@Narsil @ArthurZucker @younesbelkada

### Information

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

### Tasks

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

### Reproduction

```
from transformers import pipeline

model_path = "cardiffnlp/twitter-xlm-roberta-base-sentiment"
sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
sentiment_task("T'estimo!")
```

### Expected behavior

[{'label': 'Positive', 'score': 0.6600581407546997}]
Hi @k3ybladewielder 
It seems that this is related to your environment, can you create a fresh environment , install `transformers` `pip install transformers` and run the script again? or alternatively uninstall the package that is causing the issue? 
Also please share with us the full trace of the error in your issue and not in the title as it is hard to understand what is going on with very few details! Thanks!<|||||>Sorry for forgot to share the full trace of error.
I did it and now, the error is:
```
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<command-3729796333060543> in <module>
      5 #model_path = 'distilbert-base-uncased-finetuned-sst-2-english' #para usar no target_lang
      6 # tokenizer = AutoTokenizer.from_pretrained(model_path)
----> 7 sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
      8 sentiment_task("T'estimo!")

/databricks/python/lib/python3.7/site-packages/transformers/pipelines/__init__.py in pipeline(task, model, config, tokenizer, feature_extractor, framework, revision, use_fast, use_auth_token, model_kwargs, **kwargs)
    500 
    501             tokenizer = AutoTokenizer.from_pretrained(
--> 502                 tokenizer_identifier, revision=revision, use_fast=use_fast, _from_pipeline=task, **tokenizer_kwargs
    503             )
    504 

/databricks/python/lib/python3.7/site-packages/transformers/models/auto/tokenization_auto.py in from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs)
    496             tokenizer_class_py, tokenizer_class_fast = TOKENIZER_MAPPING[type(config)]
    497             if tokenizer_class_fast and (use_fast or tokenizer_class_py is None):
--> 498                 return tokenizer_class_fast.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
    499             else:
    500                 if tokenizer_class_py is not None:

/databricks/python/lib/python3.7/site-packages/transformers/tokenization_utils_base.py in from_pretrained(cls, pretrained_model_name_or_path, *init_inputs, **kwargs)
   1747             *init_inputs,
   1748             use_auth_token=use_auth_token,
-> 1749             **kwargs,
   1750         )
   1751 

/databricks/python/lib/python3.7/site-packages/transformers/tokenization_utils_base.py in _from_pretrained(cls, resolved_vocab_files, pretrained_model_name_or_path, init_configuration, use_auth_token, *init_inputs, **kwargs)
   1869         # Instantiate tokenizer.
   1870         try:
-> 1871             tokenizer = cls(*init_inputs, **init_kwargs)
   1872         except OSError:
   1873             raise OSError(

/databricks/python/lib/python3.7/site-packages/transformers/models/xlm_roberta/tokenization_xlm_roberta_fast.py in __init__(self, vocab_file, tokenizer_file, bos_token, eos_token, sep_token, cls_token, unk_token, pad_token, mask_token, **kwargs)
    142             pad_token=pad_token,
    143             mask_token=mask_token,
--> 144             **kwargs,
    145         )
    146 

/databricks/python/lib/python3.7/site-packages/transformers/tokenization_utils_fast.py in __init__(self, *args, **kwargs)
    116         else:
    117             raise ValueError(
--> 118                 "Couldn't instantiate the backend tokenizer from one of: \n"
    119                 "(1) a `tokenizers` library serialization file, \n"
    120                 "(2) a slow tokenizer instance to convert or \n"

ValueError: Couldn't instantiate the backend tokenizer from one of: 
(1) a `tokenizers` library serialization file, 
(2) a slow tokenizer instance to convert or 
(3) an equivalent slow tokenizer class to instantiate and convert. 
You need to have sentencepiece installed to convert a slow tokenizer to a fast one.

```<|||||>Thanks ! 
I think if you install `sentencepiece` the error should disapear
`pip install sentencepiece`<|||||>Its works, thank you @younesbelkada 