diff --git a/torchtext/datasets/udpos.py b/torchtext/datasets/udpos.py
index 2377448939..9f5e8c667e 100644
--- a/torchtext/datasets/udpos.py
+++ b/torchtext/datasets/udpos.py
@@ -1,13 +1,17 @@
-from torchtext.utils import download_from_url, extract_archive
+from torchtext._internal.module_utils import is_module_available
+from typing import Union, Tuple
+
+if is_module_available("torchdata"):
+    from torchdata.datapipes.iter import FileOpener, HttpReader, IterableWrapper
+
 from torchtext.data.datasets_utils import (
-    _RawTextIterableDataset,
     _wrap_split_argument,
     _add_docstring_header,
-    _find_match,
     _create_dataset_directory,
-    _create_data_from_iob,
 )
 
+import os
+
 URL = 'https://bitbucket.org/sivareddyg/public/downloads/en-ud-v2.zip'
 
 MD5 = 'bdcac7c52d934656bae1699541424545'
@@ -18,19 +22,36 @@
     'test': 2077,
 }
 
+_EXTRACTED_FILES = {
+    "train": "train.txt",
+    "valid": "dev.txt",
+    "test": "test.txt"
+}
+
 
 DATASET_NAME = "UDPOS"
 
 
 @_add_docstring_header(num_lines=NUM_LINES)
 @_create_dataset_directory(dataset_name=DATASET_NAME)
-@_wrap_split_argument(('train', 'valid', 'test'))
-def UDPOS(root, split):
-    dataset_tar = download_from_url(URL, root=root, hash_value=MD5, hash_type='md5')
-    extracted_files = extract_archive(dataset_tar)
-    if split == 'valid':
-        path = _find_match("dev.txt", extracted_files)
-    else:
-        path = _find_match(split + ".txt", extracted_files)
-    return _RawTextIterableDataset(DATASET_NAME, NUM_LINES[split],
-                                   _create_data_from_iob(path))
+@_wrap_split_argument(("train", "valid", "test"))
+def UDPOS(root: str, split: Union[Tuple[str], str]):
+    if not is_module_available("torchdata"):
+        raise ModuleNotFoundError("Package `torchdata` not found. Please install following instructions at `https://github.com/pytorch/data`")
+
+    url_dp = IterableWrapper([URL])
+    cache_compressed_dp = url_dp.on_disk_cache(
+        filepath_fn=lambda x: os.path.join(root, os.path.basename(URL)),
+        hash_dict={os.path.join(root, os.path.basename(URL)): MD5},
+        hash_type="md5"
+    )
+    cache_compressed_dp = HttpReader(cache_compressed_dp).end_caching(mode="wb", same_filepath_fn=True)
+
+    cache_decompressed_dp = cache_compressed_dp.on_disk_cache(
+        filepath_fn=lambda x: os.path.join(root, _EXTRACTED_FILES[split]))
+    cache_decompressed_dp = FileOpener(cache_decompressed_dp, mode="b").read_from_zip().filter(
+        lambda x: _EXTRACTED_FILES[split] in x[0])
+    cache_decompressed_dp = cache_decompressed_dp.end_caching(mode="wb", same_filepath_fn=True)
+
+    data_dp = FileOpener(cache_decompressed_dp, mode='b')
+    return data_dp.readlines(decode=True).read_iob()