Issue: Add a Text Classification dataset: KanHope

## Adding a Dataset
- **Name:** *KanHope*
- **Description:** *A code-mixed English-Kannada dataset for Hope speech detection*
- **Paper:** *https://arxiv.org/abs/2108.04616* (I am the author of the paper}
- **Author:** *[AdeepH](https://github.com/adeepH)*
- **Data:** *https://github.com/adeepH/KanHope/tree/main/dataset*
- **Motivation:** *The dataset is amongst the very few resources available for code-mixed Dravidian languages*

- I tried following the steps as per the instructions. However, could not resolve an error. Any help would be appreciated.

- The dataset card and the scripts for the dataset *https://github.com/adeepH/datasets/tree/multilingual-hope-speech/datasets/mhs_eval*

```
Using custom data configuration default
Downloading and preparing dataset bn_hate_speech/default (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/bn_hate_speech/default/0.0.0/5f417ddc89777278abd29988f909f39495f0ec802090f7d8fa63b5bffb121762...
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-114-4a9cdb519e4c> in <module>()
      1 from datasets import load_dataset
      2 
----> 3 data = load_dataset('/content/bn')

9 frames
/usr/local/lib/python3.7/dist-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, script_version, use_auth_token, task, streaming, **config_kwargs)
    850         ignore_verifications=ignore_verifications,
    851         try_from_hf_gcs=try_from_hf_gcs,
--> 852         use_auth_token=use_auth_token,
    853     )
    854 

/usr/local/lib/python3.7/dist-packages/datasets/builder.py in download_and_prepare(self, download_config, download_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, **download_and_prepare_kwargs)
    614                     if not downloaded_from_gcs:
    615                         self._download_and_prepare(
--> 616                             dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
    617                         )
    618                     # Sync info

/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _download_and_prepare(self, dl_manager, verify_infos, **prepare_split_kwargs)
    691             try:
    692                 # Prepare split will record examples associated to the split
--> 693                 self._prepare_split(split_generator, **prepare_split_kwargs)
    694             except OSError as e:
    695                 raise OSError(

/usr/local/lib/python3.7/dist-packages/datasets/builder.py in _prepare_split(self, split_generator)
   1107                     disable=bool(logging.get_verbosity() == logging.NOTSET),
   1108                 ):
-> 1109                     example = self.info.features.encode_example(record)
   1110                     writer.write(example, key)
   1111             finally:

/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_example(self, example)
   1015         """
   1016         example = cast_to_python_objects(example)
-> 1017         return encode_nested_example(self, example)
   1018 
   1019     def encode_batch(self, batch):

/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_nested_example(schema, obj)
    863     if isinstance(schema, dict):
    864         return {
--> 865             k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)
    866         }
    867     elif isinstance(schema, (list, tuple)):

/usr/local/lib/python3.7/dist-packages/datasets/features.py in <dictcomp>(.0)
    863     if isinstance(schema, dict):
    864         return {
--> 865             k: encode_nested_example(sub_schema, sub_obj) for k, (sub_schema, sub_obj) in utils.zip_dict(schema, obj)
    866         }
    867     elif isinstance(schema, (list, tuple)):

/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_nested_example(schema, obj)
    890     # ClassLabel will convert from string to int, TranslationVariableLanguages does some checks
    891     elif isinstance(schema, (ClassLabel, TranslationVariableLanguages, Value, _ArrayXD)):
--> 892         return schema.encode_example(obj)
    893     # Other object should be directly convertible to a native Arrow type (like Translation and Translation)
    894     return obj

/usr/local/lib/python3.7/dist-packages/datasets/features.py in encode_example(self, example_data)
    665         # If a string is given, convert to associated integer
    666         if isinstance(example_data, str):
--> 667             example_data = self.str2int(example_data)
    668 
    669         # Allowing -1 to mean no label.

/usr/local/lib/python3.7/dist-packages/datasets/features.py in str2int(self, values)
    623                 if value not in self._str2int:
    624                     value = str(value).strip()
--> 625                 output.append(self._str2int[str(value)])
    626             else:
    627                 # No names provided, try to integerize

KeyError: ' '
```

Comments:
Hi ! In your script it looks like you're trying to load the dataset `bn_hate_speech,`, not KanHope.

Moreover the error `KeyError: ' '` means that you have a feature of type ClassLabel, but for a certain example of the dataset, it looks like the label is empty (it's just a string with a space). Can you make sure that the data don't have missing labels, and that your dataset script parses the labels correctly ?