diff --git a/src/refiners/foundationals/clip/tokenizer.py b/src/refiners/foundationals/clip/tokenizer.py
index 0213cfa..a160ccc 100644
--- a/src/refiners/foundationals/clip/tokenizer.py
+++ b/src/refiners/foundationals/clip/tokenizer.py
@@ -11,6 +11,9 @@ class CLIPTokenizer:
     def __init__(
         self,
         vocabulary_path: str | Path = Path(__file__).resolve().parent / "bpe_simple_vocab_16e6.txt.gz",
+        start_of_text_token_id: int = 49406,
+        end_of_text_token_id: int = 49407,
+        pad_token_id: int = 49407,
     ) -> None:
         self.vocabulary_path = vocabulary_path
         self.byte_to_unicode_mapping = self.get_bytes_to_unicode_mapping()
@@ -38,15 +41,16 @@ class CLIPTokenizer:
             pattern=r"""<\|startoftext\|>|<\|endoftext\|>|'s|'t|'re|'ve|'m|'ll|'d|[a-zA-Z]+|[0-9]|[^\s\w]+""",
             flags=re.IGNORECASE,
         )
-        self.start_of_text_token_id: int = 49406
-        self.end_of_text_token_id: int = 49407
+        self.start_of_text_token_id: int = start_of_text_token_id
+        self.end_of_text_token_id: int = end_of_text_token_id
+        self.pad_token_id: int = pad_token_id
 
     def __call__(self, text: str, sequence_length: int) -> Tensor:
         tokens = self.encode(text=text, max_length=sequence_length).unsqueeze(dim=0)
         assert (
             tokens.shape[1] <= sequence_length
         ), f"Text is too long: tokens.shape[1] > sequence_length: {tokens.shape[1]} > {sequence_length}"
-        return pad(x=tokens, pad=(0, sequence_length - tokens.shape[1]), value=self.end_of_text_token_id)
+        return pad(x=tokens, pad=(0, sequence_length - tokens.shape[1]), value=self.pad_token_id)
 
     @lru_cache()
     def get_bytes_to_unicode_mapping(self) -> dict[int, str]: