diff --git a/mindmeld/app.py b/mindmeld/app.py
index 481ffd1ab..71616cf60 100644
--- a/mindmeld/app.py
+++ b/mindmeld/app.py
@@ -245,7 +245,7 @@ def register_func(self, name=None):
         def _decorator(func):
             func_name = name or func.__name__
             if not callable(func):
-                raise TypeError("Invalid function type %s.", func_name)  # pylint: disable=W0715
+                raise TypeError(f"Invalid function type {func_name}.")
             self.registry.functions_registry[func_name] = func
 
         return _decorator
diff --git a/mindmeld/cli.py b/mindmeld/cli.py
index eb08043ca..98a26f0c8 100644
--- a/mindmeld/cli.py
+++ b/mindmeld/cli.py
@@ -780,7 +780,7 @@ def num_parser(ctx, start, port):
                 DUCKLING_VERSION,
                 os.path.basename(exec_path),
             ]
-            url = os.path.join(*url_components)
+            url = "/".join(url_components)
             logger.info(
                 "Could not find %s binary file, downloading from %s", exec_path, url
             )
diff --git a/mindmeld/constants.py b/mindmeld/constants.py
index 9cd072703..4e22d1fbd 100644
--- a/mindmeld/constants.py
+++ b/mindmeld/constants.py
@@ -21,6 +21,15 @@
 BINARIES_URL = "https://binaries.mindmeld.com"
 DUCKLING_VERSION = "20211005"
 
+EMBEDDINGS_VERSION = "6B"
+EMBEDDINGS_FILE = f"glove.{EMBEDDINGS_VERSION}.zip"
+EMBEDDINGS_URL = '/'.join([
+    BINARIES_URL,
+    "glove",
+    EMBEDDINGS_VERSION,
+    EMBEDDINGS_FILE,
+])
+
 
 # ACTIVE LEARNING CONSTANTS
 class TuneLevel(Enum):
diff --git a/mindmeld/models/containers.py b/mindmeld/models/containers.py
index 9574dd922..1675861a9 100644
--- a/mindmeld/models/containers.py
+++ b/mindmeld/models/containers.py
@@ -21,12 +21,10 @@
 from tqdm import tqdm
 
 from ._util import _is_module_available, _get_module_or_attr as _getattr
+from ..constants import EMBEDDINGS_URL
 from ..core import Bunch
 from ..exceptions import EmbeddingDownloadError
-from ..path import (
-    EMBEDDINGS_FILE_PATH,
-    EMBEDDINGS_FOLDER_PATH,
-)
+from ..path import EMBEDDINGS_FILE_PATH, EMBEDDINGS_FOLDER_PATH
 from ..resource_loader import Hasher
 
 logger = logging.getLogger(__name__)
@@ -61,7 +59,6 @@ class GloVeEmbeddingsContainer:
     """
     CONTAINER_LOOKUP = {}
 
-    GLOVE_DOWNLOAD_LINK = "http://nlp.stanford.edu/data/glove.6B.zip"
     EMBEDDING_FILE_PATH_TEMPLATE = "glove.6B.{}d.txt"
     ALLOWED_WORD_EMBEDDING_DIMENSIONS = [50, 100, 200, 300]
 
@@ -96,34 +93,24 @@ def get_pretrained_word_to_embeddings_dict(self):
 
     def _download_embeddings_and_return_zip_handle(self):
 
-        logger.info("Downloading embedding from %s", GloVeEmbeddingsContainer.GLOVE_DOWNLOAD_LINK)
+        logger.info("Downloading embedding from %s", EMBEDDINGS_URL)
 
         # Make the folder that will contain the embeddings
         if not os.path.exists(EMBEDDINGS_FOLDER_PATH):
             os.makedirs(EMBEDDINGS_FOLDER_PATH)
 
-        with TqdmUpTo(
-            unit="B", unit_scale=True, miniters=1, desc=GloVeEmbeddingsContainer.GLOVE_DOWNLOAD_LINK
-        ) as t:
+        with TqdmUpTo(unit="B", unit_scale=True, miniters=1, desc=EMBEDDINGS_URL) as t:
 
             try:
-                urlretrieve(
-                    GloVeEmbeddingsContainer.GLOVE_DOWNLOAD_LINK, EMBEDDINGS_FILE_PATH,
-                    reporthook=t.update_to
-                )
+                urlretrieve(EMBEDDINGS_URL, EMBEDDINGS_FILE_PATH, reporthook=t.update_to)
 
             except ConnectionError as e:
-                logger.error(
-                    "There was an issue downloading from this "
-                    "link %s with the following error: "
-                    "%s",
-                    GloVeEmbeddingsContainer.GLOVE_DOWNLOAD_LINK,
-                    e,
-                )
+                logger.error("Error downloading from %s: %s", EMBEDDINGS_URL, e)
                 return
 
             file_name = GloVeEmbeddingsContainer.EMBEDDING_FILE_PATH_TEMPLATE.format(
-                self.token_dimension)
+                self.token_dimension
+            )
             zip_file_object = zipfile.ZipFile(EMBEDDINGS_FILE_PATH, "r")
 
             if file_name not in zip_file_object.namelist():
diff --git a/mindmeld/models/taggers/embeddings.py b/mindmeld/models/taggers/embeddings.py
index ed7e6a959..8c8116a1f 100644
--- a/mindmeld/models/taggers/embeddings.py
+++ b/mindmeld/models/taggers/embeddings.py
@@ -24,7 +24,6 @@
 
 logger = logging.getLogger(__name__)
 
-GLOVE_DOWNLOAD_LINK = "http://nlp.stanford.edu/data/glove.6B.zip"
 EMBEDDING_FILE_PATH_TEMPLATE = "glove.6B.{}d.txt"
 ALLOWED_WORD_EMBEDDING_DIMENSIONS = [50, 100, 200, 300]
 
diff --git a/mindmeld/path.py b/mindmeld/path.py
index fc0f39200..7addd6be7 100644
--- a/mindmeld/path.py
+++ b/mindmeld/path.py
@@ -22,6 +22,7 @@
 from functools import wraps
 from importlib.machinery import SourceFileLoader
 
+from .constants import EMBEDDINGS_FILE
 from .exceptions import MindMeldImportError
 
 MINDMELD_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
@@ -129,7 +130,7 @@
 }
 
 EMBEDDINGS_FOLDER_PATH = os.path.join(MINDMELD_ROOT, "data")
-EMBEDDINGS_FILE_PATH = os.path.join(EMBEDDINGS_FOLDER_PATH, "glove.6B.zip")
+EMBEDDINGS_FILE_PATH = os.path.join(EMBEDDINGS_FOLDER_PATH, EMBEDDINGS_FILE)
 PREVIOUSLY_USED_CHAR_EMBEDDINGS_FILE_PATH = os.path.join(
     EMBEDDINGS_FOLDER_PATH, "previously_used_char_embeddings.pkl"
 )