diff --git a/src/lemonade/tools/huggingface_load.py b/src/lemonade/tools/huggingface_load.py
index 8cbec6e..617a4b3 100644
--- a/src/lemonade/tools/huggingface_load.py
+++ b/src/lemonade/tools/huggingface_load.py
@@ -6,7 +6,7 @@
 from turnkeyml.state import State
 import turnkeyml.common.status as status
 from turnkeyml.tools import Tool, FirstTool
-from lemonade.tools.adapter import ModelAdapter
+from lemonade.tools.adapter import ModelAdapter, TokenizerAdapter
 from lemonade.cache import Keys
 
 # Command line interfaces for tools will use string inputs for data
@@ -32,6 +32,26 @@ def make_example_inputs(state: State) -> Dict:
     return {"input_ids": inputs_ids}
 
 
+class HuggingfaceTokenizerAdapter(TokenizerAdapter):
+    def __init__(self, tokenizer: transformers.AutoTokenizer, device: str):
+        super().__init__()
+        self.tokenizer = tokenizer
+        self.device = device
+
+    def __call__(self, prompt, **kwargs):
+        return self.tokenizer(prompt, **kwargs).to(self.device)
+
+    def decode(self, response, **kwargs):
+        return self.tokenizer.decode(response, **kwargs)
+
+    def batch_decode(self, tokens, **kwargs):
+        return self.tokenizer.batch_decode(tokens, **kwargs)
+
+    @property
+    def eos_token_id(self):
+        return self.tokenizer.eos_token_id
+
+
 class HuggingfaceLoad(FirstTool):
     """
     Load an LLM as a torch.nn.Module using the Hugging Face transformers
@@ -167,7 +187,7 @@ def run(
 
         # Pass the model and inputs into state
         state.model = model
-        state.tokenizer = tokenizer
+        state.tokenizer = HuggingfaceTokenizerAdapter(tokenizer, device)
         state.dtype = dtype
         state.checkpoint = checkpoint
         state.device = device