diff --git a/spacy/_ml.py b/spacy/_ml.py
index 09e810a98..31e0767c7 100644
--- a/spacy/_ml.py
+++ b/spacy/_ml.py
@@ -406,15 +406,11 @@ def Tok2Vec(width, embed_size, **kwargs):
     pretrained_vectors = kwargs.get("pretrained_vectors", None)
     cnn_maxout_pieces = kwargs.get("cnn_maxout_pieces", 3)
     subword_features = kwargs.get("subword_features", True)
-    char_embed = util.env_opt("char_embed", kwargs.get("char_embed", False))
+    char_embed = kwargs.get("char_embed", False)
     conv_depth = kwargs.get("conv_depth", 4)
-    bilstm_depth = util.env_opt("bilstm_depth", kwargs.get("bilstm_depth", 0))
-    self_attn_depth = util.env_opt("self_attn_depth", kwargs.get("self_attn_depth", 0))
-    conv_window = util.env_opt("conv_window", kwargs.get("cnn_window", 1))
-    kwargs.setdefault("bilstm_depth", bilstm_depth)
-    kwargs.setdefault("self_attn_depth", self_attn_depth)
-    kwargs.setdefault("char_embed", char_embed)
-    kwargs.setdefault("conv_window", conv_window)
+    bilstm_depth = kwargs.get("bilstm_depth", 0)
+    self_attn_depth = kwargs.get("self_attn_depth", 0)
+    conv_window = kwargs.get("conv_window", 1)
     if char_embed and self_attn_depth:
         return Tok2Vec_chars_selfattention(width, embed_size, **kwargs)
     elif char_embed and bilstm_depth: