diff --git a/server/text_generation_server/models/causal_lm.py b/server/text_generation_server/models/causal_lm.py
index 685177c7..dce793f5 100644
--- a/server/text_generation_server/models/causal_lm.py
+++ b/server/text_generation_server/models/causal_lm.py
@@ -627,10 +627,11 @@ class CausalLM(Model):
     def batch_type(self) -> Type[CausalLMBatch]:
         return CausalLMBatch
 
-    def decode(self, generated_ids: List[int]) -> str:
-        return self.tokenizer.decode(
-            generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
-        )
+    # This is not used anymore
+    # def decode(self, generated_ids: List[int]) -> str:
+    #     return self.tokenizer.decode(
+    #         generated_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+    #     )
 
     def forward(
         self, input_ids, attention_mask, position_ids, past_key_values: Optional = None
diff --git a/server/text_generation_server/models/flash_causal_lm.py b/server/text_generation_server/models/flash_causal_lm.py
index 5f558caa..77125f53 100644
--- a/server/text_generation_server/models/flash_causal_lm.py
+++ b/server/text_generation_server/models/flash_causal_lm.py
@@ -827,6 +827,7 @@ class FlashCausalLM(Model):
         aliases=None,
         # Used for Santacoder override of config
         num_kv_heads=None,
+        skip_special_tokens: bool = True,
     ):
         self.process_group, rank, world_size = initialize_torch_distributed()
         if torch.cuda.is_available():
diff --git a/server/text_generation_server/models/seq2seq_lm.py b/server/text_generation_server/models/seq2seq_lm.py
index 38695b19..5d16c364 100644
--- a/server/text_generation_server/models/seq2seq_lm.py
+++ b/server/text_generation_server/models/seq2seq_lm.py
@@ -668,10 +668,11 @@ class Seq2SeqLM(Model):
     def batch_type(self) -> Type[Seq2SeqLMBatch]:
         return Seq2SeqLMBatch
 
-    def decode(self, decoder_ids: List[int]) -> str:
-        return self.tokenizer.decode(
-            decoder_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
-        )
+    # Not used anymore
+    # def decode(self, decoder_ids: List[int]) -> str:
+    #     return self.tokenizer.decode(
+    #         decoder_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False
+    #     )
 
     def forward(
         self,