diff --git a/jiant/scripts/download_data/constants.py b/jiant/scripts/download_data/constants.py
index 868728a88..8110be95e 100644
--- a/jiant/scripts/download_data/constants.py
+++ b/jiant/scripts/download_data/constants.py
@@ -1,4 +1,5 @@
-# Directly download tasks when nlp format is different than original dataset
+# Directly download tasks when not available in HF Datasets, or HF Datasets version
+#   is not suitable
 SQUAD_TASKS = {"squad_v1", "squad_v2"}
 DIRECT_SUPERGLUE_TASKS_TO_DATA_URLS = {
     "wsc": f"https://dl.fbaipublicfiles.com/glue/superglue/data/v2/WSC.zip",
diff --git a/jiant/scripts/download_data/datasets/nlp_tasks.py b/jiant/scripts/download_data/datasets/hf_datasets_tasks.py
similarity index 87%
rename from jiant/scripts/download_data/datasets/nlp_tasks.py
rename to jiant/scripts/download_data/datasets/hf_datasets_tasks.py
index 1d99dcf9b..8dd0c0271 100644
--- a/jiant/scripts/download_data/datasets/nlp_tasks.py
+++ b/jiant/scripts/download_data/datasets/hf_datasets_tasks.py
@@ -1,4 +1,4 @@
-"""Use this for tasks that can be obtained from NLP without further/special processing"""
+"""Use this for tasks that can be obtained from HF-Datasets without further/special processing"""
 
 import jiant.scripts.download_data.utils as download_utils
 import jiant.utils.python.io as py_io
@@ -21,7 +21,7 @@
 )
 
 
-NLP_CONVERSION_DICT = {
+HF_DATASETS_CONVERSION_DICT = {
     # === GLUE === #
     "cola": {
         "path": "glue",
@@ -152,24 +152,24 @@
     },
 }
 
-# NLP uses "validation", we use "val"
+# HF-Datasets uses "validation", we use "val"
 DEFAULT_PHASE_MAP = {"validation": "val"}
 
 
 def download_data_and_write_config(task_name: str, task_data_path: str, task_config_path: str):
-    nlp_conversion_metadata = NLP_CONVERSION_DICT[task_name]
-    examples_dict = download_utils.convert_nlp_dataset_to_examples(
-        path=nlp_conversion_metadata["path"],
-        name=nlp_conversion_metadata.get("name"),
-        field_map=nlp_conversion_metadata.get("field_map"),
-        label_map=nlp_conversion_metadata.get("label_map"),
-        phase_map=nlp_conversion_metadata.get("phase_map", DEFAULT_PHASE_MAP),
-        phase_list=nlp_conversion_metadata.get("phase_list"),
+    hf_datasets_conversion_metadata = HF_DATASETS_CONVERSION_DICT[task_name]
+    examples_dict = download_utils.convert_hf_dataset_to_examples(
+        path=hf_datasets_conversion_metadata["path"],
+        name=hf_datasets_conversion_metadata.get("name"),
+        field_map=hf_datasets_conversion_metadata.get("field_map"),
+        label_map=hf_datasets_conversion_metadata.get("label_map"),
+        phase_map=hf_datasets_conversion_metadata.get("phase_map", DEFAULT_PHASE_MAP),
+        phase_list=hf_datasets_conversion_metadata.get("phase_list"),
     )
     paths_dict = download_utils.write_examples_to_jsonls(
         examples_dict=examples_dict, task_data_path=task_data_path,
     )
-    jiant_task_name = nlp_conversion_metadata.get("jiant_task_name", task_name)
+    jiant_task_name = hf_datasets_conversion_metadata.get("jiant_task_name", task_name)
     py_io.write_json(
         data={"task": jiant_task_name, "paths": paths_dict, "name": task_name},
         path=task_config_path,
diff --git a/jiant/scripts/download_data/runscript.py b/jiant/scripts/download_data/runscript.py
index 5d21cc6b9..ebf988deb 100644
--- a/jiant/scripts/download_data/runscript.py
+++ b/jiant/scripts/download_data/runscript.py
@@ -2,22 +2,22 @@
 import argparse
 
 import jiant.utils.python.io as py_io
-import jiant.scripts.download_data.datasets.nlp_tasks as nlp_tasks_download
+import jiant.scripts.download_data.datasets.hf_datasets_tasks as hf_datasets_tasks_download
 import jiant.scripts.download_data.datasets.xtreme as xtreme_download
 import jiant.scripts.download_data.datasets.files_tasks as files_tasks_download
 from jiant.tasks.constants import (
     GLUE_TASKS,
     SUPERGLUE_TASKS,
-    OTHER_NLP_TASKS,
+    OTHER_HF_DATASETS_TASKS,
     XTREME_TASKS,
     BENCHMARKS,
 )
 from jiant.scripts.download_data.constants import SQUAD_TASKS, DIRECT_DOWNLOAD_TASKS
 
-# DIRECT_DOWNLOAD_TASKS need to be directly downloaded because the nlp
+# DIRECT_DOWNLOAD_TASKS need to be directly downloaded because the HF Datasets
 # implementation differs from the original dataset format
-NLP_DOWNLOADER_TASKS = (GLUE_TASKS | SUPERGLUE_TASKS | OTHER_NLP_TASKS) - DIRECT_DOWNLOAD_TASKS
-SUPPORTED_TASKS = NLP_DOWNLOADER_TASKS | XTREME_TASKS | SQUAD_TASKS | DIRECT_DOWNLOAD_TASKS
+HF_DATASETS_TASKS = (GLUE_TASKS | SUPERGLUE_TASKS | OTHER_HF_DATASETS_TASKS) - DIRECT_DOWNLOAD_TASKS
+SUPPORTED_TASKS = HF_DATASETS_TASKS | XTREME_TASKS | SQUAD_TASKS | DIRECT_DOWNLOAD_TASKS
 
 
 # noinspection PyUnusedLocal
@@ -50,8 +50,8 @@ def download_data(task_names, output_base_path):
     for i, task_name in enumerate(task_names):
         task_data_path = os.path.join(task_data_base_path, task_name)
 
-        if task_name in NLP_DOWNLOADER_TASKS:
-            nlp_tasks_download.download_data_and_write_config(
+        if task_name in HF_DATASETS_TASKS:
+            hf_datasets_tasks_download.download_data_and_write_config(
                 task_name=task_name,
                 task_data_path=task_data_path,
                 task_config_path=os.path.join(task_config_base_path, f"{task_name}_config.json"),
@@ -74,7 +74,7 @@ def download_data(task_names, output_base_path):
 
 
 def main():
-    parser = argparse.ArgumentParser(description="Download NLP datasets and generate task configs")
+    parser = argparse.ArgumentParser(description="Download datasets and generate task configs")
     subparsers = parser.add_subparsers()
     sp_list = subparsers.add_parser("list", help="list supported tasks in downloader")
     sp_download = subparsers.add_parser("download", help="download data command")
diff --git a/jiant/scripts/download_data/utils.py b/jiant/scripts/download_data/utils.py
index 2bcb3d895..25b795b3c 100644
--- a/jiant/scripts/download_data/utils.py
+++ b/jiant/scripts/download_data/utils.py
@@ -1,4 +1,4 @@
-import nlp
+import datasets
 import os
 import tarfile
 import urllib
@@ -8,15 +8,15 @@
 from jiant.utils.python.datastructures import replace_key
 
 
-def convert_nlp_dataset_to_examples(
+def convert_hf_dataset_to_examples(
     path, name=None, version=None, field_map=None, label_map=None, phase_map=None, phase_list=None
 ):
-    """Helper function for reading from nlp.load_dataset and converting to examples
+    """Helper function for reading from datasets.load_dataset and converting to examples
 
     Args:
-        path: path argument (from nlp.load_dataset)
-        name: name argument (from nlp.load_dataset)
-        version: version argument (from nlp.load_dataset)
+        path: path argument (from datasets.load_dataset)
+        name: name argument (from datasets.load_dataset)
+        version: version argument (from datasets.load_dataset)
         field_map: dictionary for renaming fields, non-exhaustive
         label_map: dictionary for replacing labels, non-exhaustive
         phase_map: dictionary for replacing phase names, non-exhaustive
@@ -25,7 +25,7 @@ def convert_nlp_dataset_to_examples(
     Returns:
         Dict[phase] -> list[examples]
     """
-    dataset = nlp.load_dataset(path=path, name=name, version=version)
+    dataset = datasets.load_dataset(path=path, name=name, version=version)
     if phase_map:
         for old_phase_name, new_phase_name in phase_map.items():
             replace_key(dataset, old_key=old_phase_name, new_key=new_phase_name)
diff --git a/jiant/tasks/constants.py b/jiant/tasks/constants.py
index 32f51aa05..f2783d733 100644
--- a/jiant/tasks/constants.py
+++ b/jiant/tasks/constants.py
@@ -25,7 +25,7 @@
     "superglue_winogender_diagnostics",
 }
 
-OTHER_NLP_TASKS = {
+OTHER_HF_DATASETS_TASKS = {
     "snli",
     "commonsenseqa",
     "hellaswag",
diff --git a/jiant/tasks/lib/commonsenseqa.py b/jiant/tasks/lib/commonsenseqa.py
index b362002db..c03506eb1 100644
--- a/jiant/tasks/lib/commonsenseqa.py
+++ b/jiant/tasks/lib/commonsenseqa.py
@@ -55,13 +55,13 @@ def _create_examples(cls, lines, set_type):
 
     @classmethod
     def _create_example(cls, raw_example, set_type, i):
-        # Use heuristic for determining original or NLP format
+        # Use heuristic for determining original or HF Datasets format
         if isinstance(raw_example["question"], dict):
             return cls._create_example_from_original_format(
                 raw_example=raw_example, set_type=set_type, i=i,
             )
         elif isinstance(raw_example["question"], str):
-            return cls._create_example_from_nlp_format(
+            return cls._create_example_from_hf_datasets_format(
                 raw_example=raw_example, set_type=set_type, i=i,
             )
         else:
@@ -80,8 +80,8 @@ def _create_example_from_original_format(cls, raw_example, set_type, i):
         )
 
     @classmethod
-    def _create_example_from_nlp_format(cls, raw_example, set_type, i):
-        """Return question and choices from NLP example format"""
+    def _create_example_from_hf_datasets_format(cls, raw_example, set_type, i):
+        """Return question and choices from HF Datasets example format"""
         return Example(
             guid="%s-%s" % (set_type, i),
             prompt=raw_example["question"],
diff --git a/jiant/tasks/lib/snli.py b/jiant/tasks/lib/snli.py
index 197087b94..ccc1fbb32 100644
--- a/jiant/tasks/lib/snli.py
+++ b/jiant/tasks/lib/snli.py
@@ -105,7 +105,7 @@ def _create_examples(cls, lines, set_type):
                     )
                 )
             else:
-                # Loading from NLP data
+                # Loading from HF Datasets data
                 if line["label"] == -1:
                     continue
                 examples.append(
diff --git a/jiant/tasks/lib/socialiqa.py b/jiant/tasks/lib/socialiqa.py
index dc3fe3692..71af81e58 100644
--- a/jiant/tasks/lib/socialiqa.py
+++ b/jiant/tasks/lib/socialiqa.py
@@ -50,15 +50,15 @@ def get_test_examples(self):
     def _create_examples(cls, lines, set_type):
         examples = []
         answer_key_ls = ["answerA", "answerB", "answerC"]
-        nlp_label_map = {
+        hf_datasets_label_map = {
             "1\n": "A",
             "2\n": "B",
             "3\n": "C",
         }
         for i, line in enumerate(lines):
             if "label" in line:
-                # Loading from NLP data
-                label = nlp_label_map[line["label"]]
+                # Loading from HF Datasets data
+                label = hf_datasets_label_map[line["label"]]
             else:
                 # Loading from original data
                 label = line["correct"]
diff --git a/requirements-no-torch.txt b/requirements-no-torch.txt
index 3ed44cb7a..33619155d 100644
--- a/requirements-no-torch.txt
+++ b/requirements-no-torch.txt
@@ -2,7 +2,7 @@ attrs==19.3.0
 bs4==0.0.1
 jsonnet==0.15.0
 lxml==4.5.1
-nlp==0.4.0
+datasets==1.1.2
 nltk>=3.5
 numexpr==2.7.1
 numpy==1.18.4
diff --git a/setup.py b/setup.py
index 8f699cdb4..1a627b8b2 100644
--- a/setup.py
+++ b/setup.py
@@ -56,7 +56,7 @@
         "bs4 == 0.0.1",
         "jsonnet == 0.15.0",
         "lxml == 4.5.1",
-        "nlp == 0.4.0",
+        "datasets == 1.1.2",
         "nltk >= 3.5",
         "numexpr == 2.7.1",
         "numpy == 1.18.4",