fix pre-existing test broken by VLM detection

Wrap AutoConfig.from_pretrained in try/except in
_load_model_memory_efficient so mock/dummy model paths
don't crash the VLM detection check.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: RobotSail

src/mini_trainer/osft_utils.py

@@ -775,11 +775,17 @@ def _load_model_memory_efficient(
             log_rank_0(f"📥 Loading base model to CPU in {load_dtype}...")
 
             # Check if this is a VLM wrapping a CausalLM text backbone
-            from transformers import AutoConfig
+            _is_vlm = False
+            try:
+                from transformers import AutoConfig
 
-            _pre_config = AutoConfig.from_pretrained(pretrained_model_name_or_path, trust_remote_code=True)
+                _pre_config = AutoConfig.from_pretrained(pretrained_model_name_or_path, trust_remote_code=True)
+                _is_vlm = is_vlm_with_causal_lm(_pre_config)
+            except (OSError, ValueError):
+                # Config loading can fail for local-only or mock paths
+                pass
 
-            if is_vlm_with_causal_lm(_pre_config):
+            if _is_vlm:
                 log_rank_0("🔄 VLM detected – extracting CausalLM text backbone for OSFT")
                 # Filter out pretrained_model_name_or_path to avoid duplicate
                 # argument since it's passed positionally to extract_causal_lm_from_vlm

tests/test_osft.py

@@ -19,18 +19,24 @@
 
 import mini_trainer.osft_utils as osft_module
 from mini_trainer.api_train import run_training
-from mini_trainer.osft_utils import (MODEL_CONFIGS,
-                                     _get_model_patterns_from_name,
-                                     _load_model_memory_efficient,
-                                     auto_generate_target_osft_config,
-                                     create_osft_model_class, get_model_config,
-                                     is_osft_param, optim_wrapper)
+from mini_trainer.osft_utils import (
+    MODEL_CONFIGS,
+    _get_model_patterns_from_name,
+    _load_model_memory_efficient,
+    auto_generate_target_osft_config,
+    create_osft_model_class,
+    get_model_config,
+    is_osft_param,
+    optim_wrapper,
+)
 from mini_trainer.setup_model_for_training import setup_model
 from mini_trainer.training_types import TorchrunArgs, TrainingArgs
-from tests.test_utils.orthogonality import (OrthogonalityTracker,
-                                            check_gradient_orthogonality,
-                                            check_parameter_orthogonality,
-                                            compute_angle_differences)
+from tests.test_utils.orthogonality import (
+    OrthogonalityTracker,
+    check_gradient_orthogonality,
+    check_parameter_orthogonality,
+    compute_angle_differences,
+)
 
 
 class TestOSFTAPIValidation: