Silence peft target_parameters RuntimeWarning for MoE models (#4008)

* Silence peft target_parameters RuntimeWarning for MoE models

Wrap _get_peft_model calls with warnings.catch_warnings() to suppress
the "target_parameters were set but no parameter was matched" warning.
This fires on MoE models where expert layers use nn.Parameter naming
that peft warns about but handles correctly.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: Daniel Hanchen <danielhanchen@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

unsloth/models/llama.py

@@ -3072,7 +3072,14 @@ class FastLlamaModel:
                 gc.collect()
                 clean_gpu_cache()
 
-        model = _get_peft_model(model, lora_config)
+        import warnings as _w
+
+        with _w.catch_warnings():
+            _w.filterwarnings(
+                "ignore",
+                message = ".*target_parameters.*were set but no parameter was matched.*",
+            )
+            model = _get_peft_model(model, lora_config)
         # Fix LoraConfig.auto_mapping is None
         fix_lora_auto_mapping(model)
 

unsloth/models/vision.py

@@ -1209,7 +1209,14 @@ class FastBaseModel:
             model,
             use_gradient_checkpointing = use_gradient_checkpointing,
         )
-        model = _get_peft_model(model, lora_config)
+        import warnings as _w
+
+        with _w.catch_warnings():
+            _w.filterwarnings(
+                "ignore",
+                message = ".*target_parameters.*were set but no parameter was matched.*",
+            )
+            model = _get_peft_model(model, lora_config)
         # Apply QAT + LoRA if specified
         if qat_scheme is not None:
             print("Unsloth: Applying QAT to mitigate quantization degradation")