seq2seq example with T5 does not run due to issue with loading tokernizer
## Environment info
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- `transformers` version: 4.3.3
- Platform: linux
- Python version: 3.7
- PyTorch version (GPU?): 1.8
- Tensorflow version (GPU?): - 
- Using GPU in script?: - 
- Using distributed or parallel set-up in script?: - 

### 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: @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

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@patrickvonplaten, @patil-suraj
## Information
Hi
I am trying to run run_seq2seq.py example on mt5 model 

` python run_seq2seq.py --model_name_or_path google/mt5-small --dataset_name wmt16 --dataset_config_name ro-en --source_prefix "translate English to Romanian: " --task translation_en_to_ro   --output_dir /test/test_large  --do_train --do_eval --predict_with_generate   --max_train_samples 500  --max_val_samples 500 --tokenizer_name google/mt5-small 
`

getting this error:

```
Traceback (most recent call last):
  File "run_seq2seq.py", line 539, in <module>
    main()
  File "run_seq2seq.py", line 309, in main
    use_auth_token=True if model_args.use_auth_token else None,
  File "/dara/libs/anaconda3/envs/fast/lib/python3.7/site-packages/transformers/models/auto/tokenization_auto.py", line 379, in from_pretrained
    return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
  File "/dara/libs/anaconda3/envs/fast/lib/python3.7/site-packages/transformers/tokenization_utils_base.py", line 1789, in from_pretrained
    resolved_vocab_files, pretrained_model_name_or_path, init_configuration, *init_inputs, **kwargs
  File "/dara/libs/anaconda3/envs/fast/lib/python3.7/site-packages/transformers/tokenization_utils_base.py", line 1860, in _from_pretrained
    tokenizer = cls(*init_inputs, **init_kwargs)
  File "/dara/libs/anaconda3/envs/fast/lib/python3.7/site-packages/transformers/models/t5/tokenization_t5_fast.py", line 147, in __init__
    **kwargs,
  File "/dara/libs/anaconda3/envs/fast/lib/python3.7/site-packages/transformers/tokenization_utils_fast.py", line 103, in __init__
    "Couldn't instantiate the backend tokenizer from one of: "
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.
```

thank you for your help 


solved with installing sentencepiece, I appreciate adding a file mentioning requirements.txt thanks <|||||>Hi @dorost1234 ,
Glad you resolved the issue. Your `transformers` version is old, we have now added the  `sentencepiece` dependency in `requirements.txt`.
https://github.com/huggingface/transformers/blob/master/examples/seq2seq/requirements.txt#L2