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.

unsloth/models/llama.py

@@ -3070,7 +3070,10 @@ 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 +1209,10 @@ 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")