ValueError: Couldn't instantiate the backend tokenizer while loading model tokenizer
## Environment info
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     Don't forget to fill out the missing fields in that output! -->

- `transformers` version: 4.2.2
- Platform: Colab
- Python version: 
- PyTorch version (GPU?):
- Tensorflow version (GPU?):
- Using GPU in script?:
- Using distributed or parallel set-up in script?:


### Who can help
@mfuntowicz @patrickvonplaten
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 albert, bert, GPT2, XLM: @LysandreJik
 tokenizers: @mfuntowicz
 Trainer: @sgugger
 Speed and Memory Benchmarks: @patrickvonplaten
 Model Cards: @julien-c
 TextGeneration: @TevenLeScao
 examples/distillation: @VictorSanh
 nlp datasets: [different repo](https://github.com/huggingface/nlp)
 rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)
 Text Generation: @patrickvonplaten @TevenLeScao
 Blenderbot: @patrickvonplaten
 Bart: @patrickvonplaten
 Marian: @patrickvonplaten
 Pegasus: @patrickvonplaten
 mBART: @patrickvonplaten
 T5: @patrickvonplaten
 Longformer/Reformer: @patrickvonplaten
 TransfoXL/XLNet: @TevenLeScao
 RAG: @patrickvonplaten, @lhoestq
 FSMT: @stas00
 examples/seq2seq: @patil-suraj
 examples/bert-loses-patience: @JetRunner
 ray/raytune: @richardliaw @amogkam
 tensorflow: @jplu
 examples/token-classification: @stefan-it
 documentation: @sgugger
 -->

## Information

Model I am using (Bert, XLNet ...):
T5
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
https://github.com/allenai/unifiedqa Loading the model mentioned here for tokenizer does not work
The tasks I am working on is:
* [x] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1.  Follow the instructions here https://github.com/allenai/unifiedqa to get the sample code
2. Copy paste it in Colab to run it. 

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```
from transformers import AutoTokenizer, T5ForConditionalGeneration

model_name = "allenai/unifiedqa-t5-small" # you can specify the model size here
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = T5ForConditionalGeneration.from_pretrained(model_name)

def run_model(input_string, **generator_args):
    input_ids = tokenizer.encode(input_string, return_tensors="pt")
    res = model.generate(input_ids, **generator_args)
    return tokenizer.batch_decode(res, skip_special_tokens=True)
```
## Expected behavior
The following code should load the model without errors. 

## Error
But the following error is obtained: 
```
ValueError                                Traceback (most recent call last)
<ipython-input-4-ee10e1c1c77e> in <module>()
      2 
      3 model_name = "allenai/unifiedqa-t5-small" # you can specify the model size here
----> 4 tokenizer = AutoTokenizer.from_pretrained(model_name)
      5 model = T5ForConditionalGeneration.from_pretrained(model_name)
      6 

4 frames
/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils_fast.py in __init__(self, *args, **kwargs)
     94         else:
     95             raise ValueError(
---> 96                 "Couldn't instantiate the backend tokenizer from one of: "
     97                 "(1) a `tokenizers` library serialization file, "
     98                 "(2) a slow tokenizer instance to convert or "

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.
```

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

Hey @rsanjaykamath, 

I cannot reproduce the error on `master`. When running:

```python
from transformers import AutoTokenizer, T5ForConditionalGeneration

model_name = "allenai/unifiedqa-t5-small" # you can specify the model size here
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = T5ForConditionalGeneration.from_pretrained(model_name)
```

I don't encounter any errors...could you try to update transformers to the newest version and try again?<|||||>Hi @patrickvonplaten ,

That's strange. I just tried it on Colab with the version 4.2.2 of transformers and the same error occurs again. 
Have you tried it on colab? or local machine? 
<|||||>I see it's the classic sentencepiece error - I should have better read your error message ;-)

Here the colab to show how it works: https://colab.research.google.com/drive/1QybYdj-1bW0MHD0cutWBPWas5IFEhSjC?usp=sharing<|||||>Also see: https://github.com/huggingface/transformers/issues/8963<|||||>Ok got it. Installing sentencepiece and restarting the kernel did the trick for me. 

Thanks for your help :) Closing the issue. <|||||>I think the error message should be more clear 