diff --git a/allennlp/data/dataset_readers/huggingface_datasets_reader.py b/allennlp/data/dataset_readers/huggingface_datasets_reader.py
index b1cba0a3471..42f11f7780d 100644
--- a/allennlp/data/dataset_readers/huggingface_datasets_reader.py
+++ b/allennlp/data/dataset_readers/huggingface_datasets_reader.py
@@ -1,14 +1,16 @@
 from typing import Iterable, Optional
 
+import datasets
 from allennlp.data import DatasetReader, Token, Field
 from allennlp.data.fields import TextField, LabelField, ListField
 from allennlp.data.instance import Instance
-from datasets import load_dataset, Dataset, DatasetDict
+from datasets import load_dataset, Dataset, DatasetDict, Split
 from datasets.features import ClassLabel, Sequence, Translation, TranslationVariableLanguages
 from datasets.features import Value
 
-# TODO pab complete the documentation comments
-class HuggingfaceDatasetSplitReader(DatasetReader):
+
+# TODO pab-vmware complete the documentation comments
+class HuggingfaceDatasetReader(DatasetReader):
     """
     This reader implementation wraps the huggingface datasets package
     to utilize it's dataset management functionality and load the information in AllenNLP friendly formats
@@ -44,15 +46,17 @@ class HuggingfaceDatasetSplitReader(DatasetReader):
         pre_load     : `bool`, optional (default='False`)
     """
 
+    SUPPORTED_SPLITS = [Split.TRAIN, Split.TEST, Split.VALIDATION]
+
     def __init__(
-        self,
-        max_instances: Optional[int] = None,
-        manual_distributed_sharding: bool = False,
-        manual_multiprocess_sharding: bool = False,
-        serialization_dir: Optional[str] = None,
-        dataset_name: str = None,
-        config_name: Optional[str] = None,
-        pre_load: Optional[bool] = False
+            self,
+            max_instances: Optional[int] = None,
+            manual_distributed_sharding: bool = False,
+            manual_multiprocess_sharding: bool = False,
+            serialization_dir: Optional[str] = None,
+            dataset_name: str = None,
+            config_name: Optional[str] = None,
+            pre_load: Optional[bool] = False
     ) -> None:
         super().__init__(
             max_instances,
@@ -77,22 +81,29 @@ def load_dataset(self):
         else:
             self.datasets = load_dataset(self.dataset_name)
 
-    def load_dataset_split(self, split):
-        if self.config_name is not None:
-            self.datasets[split] = load_dataset(self.dataset_name, self.config_name, split=split)
+    def load_dataset_split(self, split: str):
+        # TODO add support for datasets.split.NamedSplit
+        if split in self.SUPPORTED_SPLITS:
+            if self.config_name is not None:
+                self.datasets[split] = load_dataset(self.dataset_name, self.config_name, split=split)
+            else:
+                self.datasets[split] = load_dataset(self.dataset_name, split=split)
         else:
-            self.datasets[split] = load_dataset(self.dataset_name, split=split)
+            raise ValueError(f"Only default splits:{self.SUPPORTED_SPLITS} are currently supported.")
 
-    def _read(self, file_path) -> Iterable[Instance]:
+    def _read(self, file_path: str) -> Iterable[Instance]:
         """
         Reads the dataset and converts the entry to AllenNLP friendly instance
         """
+        if file_path is None:
+            raise ValueError("parameter split cannot be None")
+
+        # If split is not loaded, load the specific split
         if file_path not in self.datasets:
             self.load_dataset_split(file_path)
 
-        if self.datasets is not None and self.datasets[file_path] is not None:
-            for entry in self.datasets[file_path]:
-                yield self.text_to_instance(entry)
+        for entry in self.datasets[file_path]:
+            yield self.text_to_instance(entry)
 
     def raise_feature_not_supported_value_error(self, value):
         raise ValueError(f"Datasets feature type {type(value)} is not supported yet.")
@@ -179,7 +190,6 @@ def text_to_instance(self, *inputs) -> Instance:
                     else:
                         self.raise_feature_not_supported_value_error(value)
 
-
                 # datasets.Translation cannot be mapped directly
                 # but it's dict structure can be mapped to a ListField of 2 ListField
                 elif isinstance(value, Translation):
diff --git a/tests/data/dataset_readers/huggingface_datasets_test.py b/tests/data/dataset_readers/huggingface_datasets_test.py
index 688dc2d110a..6f29a081498 100644
--- a/tests/data/dataset_readers/huggingface_datasets_test.py
+++ b/tests/data/dataset_readers/huggingface_datasets_test.py
@@ -1,13 +1,12 @@
 import pytest
 
-from allennlp.data.dataset_readers.huggingface_datasets_reader import HuggingfaceDatasetSplitReader
+from allennlp.data.dataset_readers.huggingface_datasets_reader import HuggingfaceDatasetReader
 import logging
 
 logger = logging.getLogger(__name__)
 
 
-# TODO these UTs are actually downloading the datasets and will be very very slow
-# TODO add UT were we compare huggingface wrapped reader with an explicitly coded builder
+# TODO add UT were we compare huggingface wrapped reader with an explicitly coded dataset
 class HuggingfaceDatasetSplitReaderTest:
 
     """
@@ -15,7 +14,7 @@ class HuggingfaceDatasetSplitReaderTest:
     """
     @pytest.mark.parametrize("dataset, config, split", (("glue", "cola", "train"), ("glue", "cola", "test")))
     def test_read_for_datasets_requiring_config(self, dataset, config, split):
-        huggingface_reader = HuggingfaceDatasetSplitReader(dataset_name=dataset, config_name=config)
+        huggingface_reader = HuggingfaceDatasetReader(dataset_name=dataset, config_name=config)
         instances = list(huggingface_reader.read(split))
         assert len(instances) == len(huggingface_reader.datasets[split])
         print(instances[0], print(huggingface_reader.datasets[split][0]))