Tokenizer pickling issue fix not landed in `nlp` yet? 
 Unless I recreate an arrow_dataset from my loaded nlp dataset myself (which I think does not use the cache by default), I get the following error when applying the map function:

```
dataset = nlp.load_dataset('cos_e')
tokenizer = GPT2TokenizerFast.from_pretrained('gpt2', cache_dir=cache_dir)

for split in dataset.keys():
    dataset[split].map(lambda x: some_function(x, tokenizer))
```
```
06/09/2020 10:09:19 - INFO - nlp.builder -   Constructing Dataset for split train[:10], from /home/sarahw/.cache/huggingface/datasets/cos_e/default/0.0.1
Traceback (most recent call last):
  File "generation/input_to_label_and_rationale.py", line 390, in <module>
    main()
  File "generation/input_to_label_and_rationale.py", line 263, in main
    dataset[split] = dataset[split].map(lambda x: input_to_explanation_plus_label(x, tokenizer, max_length, datasource=data_args.task_name, wt5=(model_class=='t5'), expl_only=model_args.rationale_only), batched=False)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/site-packages/nlp/arrow_dataset.py", line 522, in map
    cache_file_name = self._get_cache_file_path(function, cache_kwargs)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/site-packages/nlp/arrow_dataset.py", line 381, in _get_cache_file_path
    function_bytes = dumps(function)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/site-packages/nlp/utils/py_utils.py", line 257, in dumps
    dump(obj, file)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/site-packages/nlp/utils/py_utils.py", line 250, in dump
    Pickler(file).dump(obj)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/site-packages/dill/_dill.py", line 445, in dump
    StockPickler.dump(self, obj)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 485, in dump
    self.save(obj)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/site-packages/dill/_dill.py", line 1410, in save_function
    pickler.save_reduce(_create_function, (obj.__code__,
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 690, in save_reduce
    save(args)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 899, in save_tuple
    save(element)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 899, in save_tuple
    save(element)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/site-packages/dill/_dill.py", line 1147, in save_cell
    pickler.save_reduce(_create_cell, (f,), obj=obj)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 690, in save_reduce
    save(args)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 884, in save_tuple
    save(element)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 601, in save
    self.save_reduce(obj=obj, *rv)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 715, in save_reduce
    save(state)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/site-packages/dill/_dill.py", line 912, in save_module_dict
    StockPickler.save_dict(pickler, obj)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 969, in save_dict
    self._batch_setitems(obj.items())
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 995, in _batch_setitems
    save(v)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 601, in save
    self.save_reduce(obj=obj, *rv)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 715, in save_reduce
    save(state)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 558, in save
    f(self, obj)  # Call unbound method with explicit self
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/site-packages/dill/_dill.py", line 912, in save_module_dict
    StockPickler.save_dict(pickler, obj)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 969, in save_dict
    self._batch_setitems(obj.items())
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 995, in _batch_setitems
    save(v)
  File "/home/sarahw/miniconda3/envs/project_huggingface/lib/python3.8/pickle.py", line 576, in save
    rv = reduce(self.proto)
TypeError: cannot pickle 'Tokenizer' object
```
Fix seems to be in the tokenizers [`0.8.0.dev1 pre-release`](https://github.com/huggingface/tokenizers/issues/87), which I can't install with any package managers.  
 If others run into this issue, a quick fix is to use python 3.6 instead of 3.7+. Serialization differences between the 3rd party `dataclasses` package for 3.6 and the built in `dataclasses` in 3.7+ cause the issue.

Probably a dumb fix, but it works for me.