diff --git a/spacy/_ml.py b/spacy/_ml.py
index 3db28ced5..2d4064652 100644
--- a/spacy/_ml.py
+++ b/spacy/_ml.py
@@ -360,7 +360,7 @@ def Tok2Vec(width, embed_size, **kwargs):
                 "config": {
                     "vectors_name": pretrained_vectors,
                     "width": width,
-                    "column": cols.index("ID")
+                    "column": cols.index("ID"),
                 },
             }
     if cnn_maxout_pieces >= 2:
diff --git a/spacy/ml/tok2vec.py b/spacy/ml/tok2vec.py
index d24b9d0c7..4f3cd458d 100644
--- a/spacy/ml/tok2vec.py
+++ b/spacy/ml/tok2vec.py
@@ -45,12 +45,15 @@ def MultiHashEmbed(config):
 
     norm = HashEmbed(width, rows, column=cols.index("NORM"), name="embed_norm")
     if config["use_subwords"]:
-        prefix = HashEmbed(width, rows // 2,
-            column=cols.index("PREFIX"), name="embed_prefix")
-        suffix = HashEmbed(width, rows // 2,
-            column=cols.index("SUFFIX"), name="embed_suffix")
-        shape = HashEmbed(width, rows // 2,
-            column=cols.index("SHAPE"), name="embed_shape")
+        prefix = HashEmbed(
+            width, rows // 2, column=cols.index("PREFIX"), name="embed_prefix"
+        )
+        suffix = HashEmbed(
+            width, rows // 2, column=cols.index("SUFFIX"), name="embed_suffix"
+        )
+        shape = HashEmbed(
+            width, rows // 2, column=cols.index("SHAPE"), name="embed_shape"
+        )
     if config.get("@pretrained_vectors"):
         glove = make_layer(config["@pretrained_vectors"])
     mix = make_layer(config["@mix"])
@@ -60,20 +63,16 @@ def MultiHashEmbed(config):
             mix._layers[0].nI = width * 5
             layer = uniqued(
                 (glove | norm | prefix | suffix | shape) >> mix,
-                column=cols.index("ORTH")
+                column=cols.index("ORTH"),
             )
         elif config["use_subwords"]:
             mix._layers[0].nI = width * 4
             layer = uniqued(
-                (norm | prefix | suffix | shape) >> mix,
-                column=cols.index("ORTH")
+                (norm | prefix | suffix | shape) >> mix, column=cols.index("ORTH")
             )
         elif config["@pretrained_vectors"]:
             mix._layers[0].nI = width * 2
-            embed = uniqued(
-                (glove | norm) >> mix,
-                column=cols.index("ORTH"),
-            )
+            embed = uniqued((glove | norm) >> mix, column=cols.index("ORTH"),)
         else:
             embed = norm
     layer.cfg = config
diff --git a/spacy/tests/pipeline/test_functions.py b/spacy/tests/pipeline/test_functions.py
index fbb88ade2..5b5fcd2fd 100644
--- a/spacy/tests/pipeline/test_functions.py
+++ b/spacy/tests/pipeline/test_functions.py
@@ -21,4 +21,14 @@ def doc(en_tokenizer):
 def test_merge_subtokens(doc):
     doc = merge_subtokens(doc)
     # get_doc() doesn't set spaces, so the result is "And a third ."
-    assert [t.text for t in doc] == ["This", "is", "a sentence", ".", "This", "is", "another sentence", ".", "And a third ."]
+    assert [t.text for t in doc] == [
+        "This",
+        "is",
+        "a sentence",
+        ".",
+        "This",
+        "is",
+        "another sentence",
+        ".",
+        "And a third .",
+    ]