diff --git a/convert.py b/convert.py
index 8bc06120d..7a35a99a2 100644
--- a/convert.py
+++ b/convert.py
@@ -243,7 +243,7 @@ class Params:
 
 
 class SentencePieceVocab:
-    def __init__(self, fname_tokenizer: Path, fname_added_tokens: Optional[Path], fname_special_tokens: Optional[Path], vocabtype: Optional[str]) -> None:
+    def __init__(self, fname_tokenizer: Path, fname_added_tokens: Optional[Path], fname_special_tokens: Optional[Path], fname_tokenizer_config: Optional[Path], vocabtype: Optional[str]) -> None:
         self.vocabtype = vocabtype
         if self.vocabtype == "bpe":
           self.sentencepiece_tokenizer = json.loads(open(str(fname_tokenizer)).read())
@@ -268,13 +268,40 @@ class SentencePieceVocab:
         self.vocab_size: int = self.vocab_size_base + len(self.added_tokens_list)
         self.fname_tokenizer = fname_tokenizer
         self.fname_added_tokens = fname_added_tokens
-        special_tokens: Dict[str, Dict[str, Any]]
+        self.special_tokens_map: Dict[int, str] = {}
+
+        TOKEN_NAME_TO_ID: Dict[str, int] = {
+            "unk_token": self.sentencepiece_tokenizer.unk_id(),
+            "bos_token": self.sentencepiece_tokenizer.bos_id(),
+            "eos_token": self.sentencepiece_tokenizer.eos_id(),
+            "pad_token": self.sentencepiece_tokenizer.pad_id()
+        }
+
+        tokenizer_config: Dict[str, Any]
+        if fname_tokenizer_config is not None:
+            tokenizer_config = json.load(open(fname_tokenizer_config))
+        else:
+            tokenizer_config = {}
+        for key, value in tokenizer_config.items():
+            assert isinstance(value, dict) or isinstance(value, str)
+            if key not in TOKEN_NAME_TO_ID or TOKEN_NAME_TO_ID[key] == -1:
+                continue
+            self.special_tokens_map[TOKEN_NAME_TO_ID[key]] = value["content"] if isinstance(value, dict) else value
+
+        special_tokens: Dict[str, Any]
         if fname_special_tokens is not None:
             special_tokens = json.load(open(fname_special_tokens))
         else:
             special_tokens = {}
-        token_name_to_id = {"unk_token": self.sentencepiece_tokenizer.unk_id(), "bos_token": self.sentencepiece_tokenizer.bos_id(), "eos_token": self.sentencepiece_tokenizer.eos_id(), "pad_token": self.sentencepiece_tokenizer.pad_id()}
-        self.special_tokens_map = {token_name_to_id[token_name]: info["content"] if isinstance(info, dict) else info for token_name, info in special_tokens.items() if token_name in token_name_to_id and token_name_to_id[token_name] != -1}
+        for key, value in special_tokens.items():
+            assert isinstance(value, dict) or isinstance(value, str)
+            if key not in TOKEN_NAME_TO_ID:
+                continue
+            token_id = TOKEN_NAME_TO_ID[key]
+            if token_id == -1 or token_id in self.special_tokens_map:
+                continue
+            self.special_tokens_map[token_id] = value["content"] if isinstance(value, dict) else value
+
         self.vocab_special_size: int = len(self.added_tokens_list) + len(self.special_tokens_map)
 
     def sentencepiece_tokens(self) -> Iterable[Tuple[bytes, float]]:
@@ -1282,7 +1309,7 @@ def load_vocab(path: Path, vocabtype: Optional[str]) -> SentencePieceVocab:
     special_tokens_path = path.parent / "special_tokens_map.json"
     tokenizer_config_path = path.parent / "tokenizer_config.json"
     print(f"Loading vocab file {path}")
-    return SentencePieceVocab(path, added_tokens_path if added_tokens_path.exists() else None, special_tokens_path if special_tokens_path.exists() else tokenizer_config_path if tokenizer_config_path.exists() else None,
+    return SentencePieceVocab(path, added_tokens_path if added_tokens_path.exists() else None, special_tokens_path if special_tokens_path.exists() else None, tokenizer_config_path if tokenizer_config_path.exists() else None,
                               vocabtype)