diff --git a/prompting/llms/hf.py b/prompting/llms/hf.py
index be46dc1b8..d2a095405 100644
--- a/prompting/llms/hf.py
+++ b/prompting/llms/hf.py
@@ -207,7 +207,11 @@ def __call__(self, messages: List[Dict[str, str]]):
         return self.forward(messages=messages)
 
     def _make_prompt(self, messages: List[Dict[str, str]]):
-        return self.llm_pipeline.tokenizer.apply_chat_template(
+        # The tokenizer.tokenizer is used for a integration with vllm and the mock pipeline, for real hf application, use:
+        # return self.llm_pipeline.tokenizer.apply_chat_template(
+        #     messages, tokenize=False, add_generation_prompt=True
+        # )
+        return self.llm_pipeline.tokenizer.tokenizer.apply_chat_template(
             messages, tokenize=False, add_generation_prompt=True
         )
 
diff --git a/prompting/llms/vllm_llm.py b/prompting/llms/vllm_llm.py
index a8bf9e095..85ee7b974 100644
--- a/prompting/llms/vllm_llm.py
+++ b/prompting/llms/vllm_llm.py
@@ -67,7 +67,7 @@ def __init__(
         self.llm = load_vllm_pipeline(model_id, device, gpus, llm_max_allowed_memory_in_gb, mock)
         self.mock = mock
         self.gpus = gpus
-        self.tokenizer = self.llm.llm_engine.tokenizer
+        self.tokenizer = self.llm.llm_engine.tokenizer.tokenizer
 
     def __call__(self, composed_prompt: str, **model_kwargs: Dict) -> str:
         if self.mock:
diff --git a/prompting/mock.py b/prompting/mock.py
index cc8ea8167..34b172a82 100644
--- a/prompting/mock.py
+++ b/prompting/mock.py
@@ -30,14 +30,16 @@ class MockModel(torch.nn.Module):
     def __init__(self, phrase):
         super().__init__()
 
-        self.tokenizer = MockTokenizer()
+        self.tokenizer = SimpleNamespace(
+            tokenizer=MockTokenizer()
+        )
         self.phrase = phrase
 
     def __call__(self, messages):
         return self.forward(messages)
 
     def forward(self, messages):
-        role_tag = self.tokenizer.role_expr.format(role="assistant")
+        role_tag = self.tokenizer.tokenizer.role_expr.format(role="assistant")
         return f"{role_tag} {self.phrase}"
 
 
@@ -73,7 +75,7 @@ def forward(self, messages, **kwargs):
         return self.postprocess(output)
 
     def postprocess(self, output, **kwargs):
-        output = output.split(self.model.tokenizer.role_expr.format(role="assistant"))[
+        output = output.split(self.model.tokenizer.tokenizer.role_expr.format(role="assistant"))[
             -1
         ].strip()
         return output
diff --git a/prompting/utils/logging.py b/prompting/utils/logging.py
index 381d68b62..d7029b89c 100644
--- a/prompting/utils/logging.py
+++ b/prompting/utils/logging.py
@@ -92,10 +92,7 @@ def init_wandb(self, reinit=False):
         tags=tags,
         notes=self.config.wandb.notes,
     )
-    bt.logging.success(
-        prefix="Started a new wandb run",
-        sufix=f"<blue> {self.wandb.name} </blue>",
-    )
+    bt.logging.success(f"Started a new wandb run <blue> {self.wandb.name} </blue>")
 
 
 def reinit_wandb(self):