[examples/seq2seq/README.md] fix t5 examples
This PR:
* switches the summarization example to use CNN/DailyMail as with t5-small it provides high scores out of the box.
* fixes T5 examples to include `--source_prefix` - it's **not** optional. If you give it a try you will see that you get 10x worse bleu scores w/o it. w/ `27.6849`, w/o `2.374`
* adds a normal translation example w/o the peculiarities of MBart and T5
* reduces the default max samples to 50 so it's much faster to test quickly
* fixes the reference to the last custom dataset that I incorrectly added in the first place (was missing a username, but worked locally when I created it w/o it)
* removes the 3 `--max*samples` from this README and puts a section on how to use these in the top-level `examples/README.md`

@sgugger, @patrickvonplaten 

This looks good to me! I think it's a good idea to add `--source_prefix` for the 5 t5 checkpoints in the examples. We should specify though that it's only for these 5 checkpoints. Let's discuss summarization in the issue.<|||||>As discussed in https://github.com/huggingface/transformers/issues/10733#issuecomment-800123545 updated the summarization example to use cnn_dailymail - now the prefix works for t5! Thank you, @patrickvonplaten <|||||>Sorry for disturbing you, but has the support for MBart been removed? This model needs source_lang and target_lang arguments, but the scripts don't accept them now.<|||||>They are sill [here](https://github.com/huggingface/transformers/blob/fd1d9f1ab89805fb2a8e773edbc27531b449ddea/examples/seq2seq/run_translation.py#L96).<|||||>Thank you very much! I can copy that part into summarization file.<|||||>Sorry to disturb you again. Even after the copy of the MBart part code, the error occurred.
```py
Traceback (most recent call last):
  File "examples/seq2seq/run_summarization.py", line 609, in <module>
    main()
  File "examples/seq2seq/run_summarization.py", line 443, in main
    train_dataset = train_dataset.map(
  File "/home/zchelllo/anaconda3/envs/ex/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1407, in map
    update_data = does_function_return_dict(test_inputs, test_indices)
  File "/home/zchelllo/anaconda3/envs/ex/lib/python3.8/site-packages/datasets/arrow_dataset.py", line 1378, in does_function_return_dict
    function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
  File "examples/seq2seq/run_summarization.py", line 424, in preprocess_function
    with tokenizer.as_target_tokenizer():
  File "/home/zchelllo/anaconda3/envs/ex/lib/python3.8/contextlib.py", line 113, in __enter__
    return next(self.gen)
  File "/home/zchelllo/anaconda3/envs/ex/lib/python3.8/site-packages/transformers/models/mbart/tokenization_mbart_fast.py", line 214, in as_target_tokenizer
    self.set_tgt_lang_special_tokens(self.tgt_lang)
  File "/home/zchelllo/anaconda3/envs/ex/lib/python3.8/site-packages/transformers/models/mbart/tokenization_mbart_fast.py", line 240, in set_tgt_lang_special_tokens
    suffix_tokens_str = self.convert_ids_to_tokens(self.suffix_tokens)
  File "/home/zchelllo/anaconda3/envs/ex/lib/python3.8/site-packages/transformers/tokenization_utils_fast.py", line 286, in convert_ids_to_tokens
    index = int(index)
TypeError: int() argument must be a string, a bytes-like object or a number, not 'NoneType'
```

The command is 
```sh
CUDA_VISIBLE_DEVICES=0 python examples/seq2seq/run_summarization.py --model_name_or_path facebook/mbart-large-cc25 \
 --do_train --do_predict --train_file ../data/lang8_ja_train.csv --test_file ../data/lang8_ja_test.csv  \
--output_dir ../pre_models/mbart_lang8_ja \
--per_device_train_batch_size=4  --per_device_eval_batch_size=4  \
--predict_with_generate --text_column errorful_sent --summary_column correct_sent \
--save_steps=2000 --save_total_limit=3 --overwrite_output_dir \
--source_lang ja_XX --target_lang ja_XX
```

And the possible reason is that even I input the source and target language, these arguments haven't been sent into prepare_seq2seq_batch function in line 195 tokenization_mbart_fast.py.  The `self.src_lang` is `en_XX` and `self.tgt_lang` is `None`.<|||||>Sorry, I found that I missed this part. After copying this part, it works well! Thank you very much!
```py
 # For translation we set the codes of our source and target languages (only useful for mBART, the others will
# ignore those attributes).
if isinstance(tokenizer, (MBartTokenizer, MBartTokenizerFast)):
    if data_args.source_lang is not None:
        tokenizer.src_lang = data_args.source_lang
    if data_args.target_lang is not None:
        tokenizer.tgt_lang = data_args.target_lang
```