Upload convert_vision_model.py with huggingface_hub

convert_vision_model.py

@@ -109,13 +109,31 @@ if IS_LORA:
         with open(adapter_config_path) as f:
             adapter_config = json.load(f)
 
-        # Load base model with specific class
-        model_classes = [
-            ("Glm4vForConditionalGeneration", "transformers"),
-            ("Mistral3ForConditionalGeneration", "transformers"),
-            ("Gemma3ForConditionalGeneration", "transformers"),
-            ("AutoModelForVision2Seq", "transformers"),
-        ]
+        # Load base model with specific class - detect from model name
+        model_classes = []
+        base_lower = BASE_MODEL.lower()
+        if "ministral" in base_lower or "mistral" in base_lower:
+            model_classes = [
+                ("Mistral3ForConditionalGeneration", "transformers"),
+                ("AutoModelForCausalLM", "transformers"),
+            ]
+        elif "glm" in base_lower:
+            model_classes = [
+                ("Glm4vForConditionalGeneration", "transformers"),
+                ("AutoModelForVision2Seq", "transformers"),
+            ]
+        elif "gemma" in base_lower:
+            model_classes = [
+                ("Gemma3ForConditionalGeneration", "transformers"),
+                ("AutoModelForVision2Seq", "transformers"),
+            ]
+        else:
+            model_classes = [
+                ("AutoModelForCausalLM", "transformers"),
+                ("AutoModelForVision2Seq", "transformers"),
+            ]
+
+        print(f"  Detected model type, trying: {[c[0] for c in model_classes]}")
 
         base_model = None
         for class_name, module in model_classes: