diff --git a/src/llama_stack/providers/inline/inference/meta_reference/inference.py b/src/llama_stack/providers/inline/inference/meta_reference/inference.py
index 286335a7d..76d3fdd50 100644
--- a/src/llama_stack/providers/inline/inference/meta_reference/inference.py
+++ b/src/llama_stack/providers/inline/inference/meta_reference/inference.py
@@ -146,7 +146,7 @@ class MetaReferenceInferenceImpl(
     def check_model(self, request) -> None:
         if self.model_id is None or self.llama_model is None:
             raise RuntimeError(
-                "No avaible model yet, please register your requested model or add your model in the resouces first"
+                "No available model yet, please register your requested model or add your model in the resources first"
             )
         elif request.model != self.model_id:
             raise RuntimeError(f"Model mismatch: request model: {request.model} != loaded model: {self.model_id}")
diff --git a/src/llama_stack/providers/inline/post_training/torchtune/common/checkpointer.py b/src/llama_stack/providers/inline/post_training/torchtune/common/checkpointer.py
index af8bd2765..43e206490 100644
--- a/src/llama_stack/providers/inline/post_training/torchtune/common/checkpointer.py
+++ b/src/llama_stack/providers/inline/post_training/torchtune/common/checkpointer.py
@@ -91,7 +91,7 @@ class TorchtuneCheckpointer:
         if checkpoint_format == "meta" or checkpoint_format is None:
             self._save_meta_format_checkpoint(model_file_path, state_dict, adapter_only)
         elif checkpoint_format == "huggingface":
-            # Note: for saving hugging face format checkpoints, we only suppport saving adapter weights now
+            # Note: for saving hugging face format checkpoints, we only support saving adapter weights now
             self._save_hf_format_checkpoint(model_file_path, state_dict)
         else:
             raise ValueError(f"Unsupported checkpoint format: {format}")
diff --git a/src/llama_stack/providers/inline/post_training/torchtune/datasets/format_adapter.py b/src/llama_stack/providers/inline/post_training/torchtune/datasets/format_adapter.py
index 96dd8b8dd..47452efa4 100644
--- a/src/llama_stack/providers/inline/post_training/torchtune/datasets/format_adapter.py
+++ b/src/llama_stack/providers/inline/post_training/torchtune/datasets/format_adapter.py
@@ -25,7 +25,7 @@ def llama_stack_instruct_to_torchtune_instruct(
     )
     input_messages = json.loads(sample[ColumnName.chat_completion_input.value])
 
-    assert len(input_messages) == 1, "llama stack intruct dataset format only supports 1 user message"
+    assert len(input_messages) == 1, "llama stack instruct dataset format only supports 1 user message"
     input_message = input_messages[0]
 
     assert "content" in input_message, "content not found in input message"