diff --git a/modeling/tokenizer.py b/modeling/tokenizer.py
index 26b619f6..e6e235d7 100644
--- a/modeling/tokenizer.py
+++ b/modeling/tokenizer.py
@@ -9,7 +9,6 @@ class GenericTokenizer:
 
     def __init__(self, tokenizer: Union[Tokenizer, PreTrainedTokenizer]) -> None:
         self.tokenizer = tokenizer
-        self.valid_tokens = set(self.tokenizer.vocab.values())
 
     def __getattr__(self, name: str) -> Any:
         # Fall back to tokenizer for non-generic stuff
@@ -29,16 +28,12 @@ class GenericTokenizer:
         return ret.ids
 
     def decode(self, tokens: Union[int, List[int], torch.Tensor]) -> str:
-        return self.tokenizer.decode(tokens)
-        if isinstance(tokens, torch.Tensor):
-            tokens = tokens.cpu().tolist()
-
         if isinstance(tokens, int):
             tokens = [tokens]
-        
-        # Sometimes soft token placeholders aren't in the vocab, which causes
-        # errors on decode. Obviously we can't express these tokens as text so
-        # we can probably slice 'em out without too much issue
-        tokens = [t for t in tokens if t in self.valid_tokens]
+
+        if isinstance(tokens, list):
+            tokens = torch.tensor(tokens)
+        elif isinstance(tokens, torch.Tensor):
+            tokens = tokens.cpu()
 
         return self.tokenizer.decode(tokens)