diff --git a/src/llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device.py b/src/llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device.py
index 4506a2351..39b83a3fd 100644
--- a/src/llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device.py
+++ b/src/llama_stack/providers/inline/post_training/huggingface/recipes/finetune_single_device.py
@@ -358,6 +358,10 @@ class HFFinetuningSingleDevice:
         if peft_config:
             logger.info("Merging LoRA weights with base model")
             # TRL's merge_and_unload returns a HuggingFace model
+            # Both cast() and type: ignore are needed here:
+            # - cast() tells mypy the return type is HFAutoModel for downstream code
+            # - type: ignore suppresses errors on the merge_and_unload() call itself,
+            #   which mypy can't type-check due to TRL library's incomplete type stubs
             model_obj = cast(HFAutoModel, trainer.model.merge_and_unload())  # type: ignore[union-attr,operator]
         else:
             # trainer.model is the trained HuggingFace model
diff --git a/src/llama_stack/testing/api_recorder.py b/src/llama_stack/testing/api_recorder.py
index dfa541872..eb43019c9 100644
--- a/src/llama_stack/testing/api_recorder.py
+++ b/src/llama_stack/testing/api_recorder.py
@@ -599,6 +599,10 @@ def _combine_model_list_responses(endpoint: str, records: list[dict[str, Any]])
     if endpoint == "/api/tags":
         from ollama import ListResponse
 
+        # Both cast(Any, ...) and type: ignore are needed here:
+        # - cast(Any, ...) attempts to bypass type checking on the argument
+        # - type: ignore is still needed because mypy checks the call site independently
+        #   and reports arg-type mismatch even after casting
         body = ListResponse(models=cast(Any, ordered))  # type: ignore[arg-type]
     return {"request": canonical_req, "response": {"body": body, "is_streaming": False}}