fix: improve lora kernels failure message and handle trust_remote_code (#3378) [skip ci]

* fix: improve lora kernels failure message and handle trust_remote_code

* chore: re-order model guides

src/axolotl/monkeypatch/lora_kernels.py

@@ -169,7 +169,8 @@ def get_attention_cls_from_config(cfg: DictDefault) -> Type[nn.Module]:
         return attention_cls
     except (ImportError, AttributeError) as e:
         raise ValueError(
-            f"Could not import attention class for model_type: {model_type}. "
+            f"Axolotl could not import attention class for model_type: {model_type}. "
+            "Please raise an Issue and turn off lora kernels to continue training. "
             f"Error: {str(e)}"
         ) from e
 

src/axolotl/utils/schemas/config.py

@@ -1271,6 +1271,10 @@ class AxolotlConfigWCapabilities(AxolotlInputConfig):
             ):
                 return data
 
+            # Skip if trust_remote_code is enabled, as lora kernels are not compatible
+            if data.get("trust_remote_code"):
+                return data
+
             # Skip if dropout is not 0, as auto enabling it would just disable it during runtime patch checks
             if data.get("lora_dropout") != 0:
                 return data

src/axolotl/utils/schemas/validation.py

@@ -690,6 +690,21 @@ class LoRAValidationMixin:
             )
         return data
 
+    @model_validator(mode="before")
+    @classmethod
+    def check_lora_kernels_trust_remote_code(cls, data):
+        if (
+            data.get("lora_mlp_kernel")
+            or data.get("lora_qkv_kernel")
+            or data.get("lora_o_kernel")
+        ) and data.get("trust_remote_code"):
+            raise ValueError(
+                "lora_mlp_kernel, lora_qkv_kernel, and lora_o_kernel are not "
+                "compatible with trust_remote_code. Please disable trust_remote_code "
+                "or explicitly set lora_*_kernel to false."
+            )
+        return data
+
 
 class RLValidationMixin:
     """Validation methods related to RL training configuration."""