diff --git a/spacy/ml/staticvectors.py b/spacy/ml/staticvectors.py
index 4c9e53563..ce2c7efff 100644
--- a/spacy/ml/staticvectors.py
+++ b/spacy/ml/staticvectors.py
@@ -37,15 +37,14 @@ def forward(
     if not len(docs):
         return _handle_empty(model.ops, model.get_dim("nO"))
     key_attr = model.attrs["key_attr"]
-    W = cast(Floats2d, model.get_param("W"))
+    W = cast(Floats2d, model.ops.as_contig(model.get_param("W")))
     V = cast(Floats2d, docs[0].vocab.vectors.data)
     mask = _get_drop_mask(model.ops, W.shape[0], model.attrs.get("dropout_rate"))
-
     rows = model.ops.flatten(
         [doc.vocab.vectors.find(keys=doc.to_array(key_attr)) for doc in docs]
     )
     output = Ragged(
-        model.ops.gemm(V[rows], W, trans2=True),
+        model.ops.gemm(model.ops.as_contig(V[rows]), W, trans2=True),
         model.ops.asarray([len(doc) for doc in docs], dtype="i")
     )
     if mask is not None:
@@ -54,7 +53,14 @@ def forward(
     def backprop(d_output: Ragged) -> List[Doc]:
         if mask is not None:
             d_output.data *= mask
-        model.inc_grad("W", model.ops.gemm(d_output.data, V[rows], trans1=True))
+        model.inc_grad(
+            "W",
+            model.ops.gemm(
+                d_output.data,
+                model.ops.as_contig(V[rows]),
+                trans1=True
+            )
+        )
         return []
 
     return output, backprop