diff --git a/convert_hf_to_gguf.py b/convert_hf_to_gguf.py
index ac353c7dda..c6724f2ed5 100755
--- a/convert_hf_to_gguf.py
+++ b/convert_hf_to_gguf.py
@@ -5160,28 +5160,6 @@ class KimiLinearModel(TextModel):
         else:
             raise NotImplementedError(f"Deepseek pre-tokenizer {tokpre!r} is not supported yet!")
 
-    @staticmethod
-    def _token_bytes_to_string(b: bytes) -> str:
-        """Convert bytes to string representation for tokenizer"""
-        return ''.join([chr(byte) if byte < 128 else f'<0x{byte:02X}>' for byte in b])
-    
-    @staticmethod  
-    def _bpe(mergeable_ranks: dict[bytes, int], token: bytes, max_rank: int | None = None) -> list[bytes]:
-        """BPE tokenization for merges extraction"""
-        parts = [bytes([b]) for b in token]
-        while True:
-            min_idx = None
-            min_rank = None
-            for i, pair in enumerate(zip(parts[:-1], parts[1:])):
-                rank = mergeable_ranks.get(pair[0] + pair[1])
-                if rank is not None and (min_rank is None or rank < min_rank):
-                    min_idx = i
-                    min_rank = rank
-            if min_rank is None or (max_rank is not None and min_rank >= max_rank):
-                break
-            parts = parts[:min_idx] + [parts[min_idx] + parts[min_idx + 1]] + parts[min_idx + 2:]
-        return parts
-
     def prepare_tensors(self):
         super().prepare_tensors()
         if self._experts is not None: