diff --git a/modeling/inference_models/hf.py b/modeling/inference_models/hf.py
index 63c0a40d..013590ef 100644
--- a/modeling/inference_models/hf.py
+++ b/modeling/inference_models/hf.py
@@ -18,20 +18,6 @@ class HFInferenceModel(InferenceModel):
         self.tokenizer = None
 
     def _post_load(self) -> None:
-        # Clean up tokens that cause issues
-        if (
-            utils.koboldai_vars.badwordsids == koboldai_settings.badwordsids_default
-            and utils.koboldai_vars.model_type not in ("gpt2", "gpt_neo", "gptj")
-        ):
-            utils.koboldai_vars.badwordsids = [
-                [v]
-                for k, v in self.tokenizer.get_vocab().items()
-                if any(c in str(k) for c in "[]")
-            ]
-
-            if utils.koboldai_vars.newlinemode == "n":
-                utils.koboldai_vars.badwordsids.append([self.tokenizer.eos_token_id])
-
         # These are model specific tokenizer overrides if a model has bad defaults
         if utils.koboldai_vars.model_type == "llama":
             self.tokenizer.decode_with_prefix_space = True
@@ -49,6 +35,20 @@ class HFInferenceModel(InferenceModel):
             # Handle </s> but don't convert newlines if using Fairseq models that have newlines trained in them
             utils.koboldai_vars.newlinemode = "ns"
 
+        # Clean up tokens that cause issues
+        if (
+            utils.koboldai_vars.badwordsids == koboldai_settings.badwordsids_default
+            and utils.koboldai_vars.model_type not in ("gpt2", "gpt_neo", "gptj")
+        ):
+            utils.koboldai_vars.badwordsids = [
+                [v]
+                for k, v in self.tokenizer.get_vocab().items()
+                if any(c in str(k) for c in "[]")
+            ]
+
+            if utils.koboldai_vars.newlinemode == "n":
+                utils.koboldai_vars.badwordsids.append([self.tokenizer.eos_token_id])
+
         return super()._post_load()
 
     def get_local_model_path(