diff --git a/docs/source/en/main_classes/executorch.md b/docs/source/en/main_classes/executorch.md
index 28e0a445e79..3178085c913 100644
--- a/docs/source/en/main_classes/executorch.md
+++ b/docs/source/en/main_classes/executorch.md
@@ -27,7 +27,7 @@ ExecuTorch introduces well defined entry points to perform model, device, and/or
 
 An integration point is being developed to ensure that 🤗 Transformers can be exported using `torch.export`. The goal of this integration is not only to enable export but also to ensure that the exported artifact can be further lowered and optimized to run efficiently in `ExecuTorch`, particularly for mobile and edge use cases.
 
-[[autodoc]] integrations.executorch.TorchExportableModuleWithStaticCache
+[[autodoc]] TorchExportableModuleWithStaticCache
     - forward
 
-[[autodoc]] integrations.executorch.convert_and_export_with_cache
+[[autodoc]] convert_and_export_with_cache
diff --git a/docs/source/en/main_classes/text_generation.md b/docs/source/en/main_classes/text_generation.md
index e2c5ce9c0ba..574e4c75a6a 100644
--- a/docs/source/en/main_classes/text_generation.md
+++ b/docs/source/en/main_classes/text_generation.md
@@ -45,17 +45,17 @@ like token streaming.
 
 ## GenerationMixin
 
-[[autodoc]] generation.GenerationMixin
+[[autodoc]] GenerationMixin
 	- generate
 	- compute_transition_scores
 
 ## TFGenerationMixin
 
-[[autodoc]] generation.TFGenerationMixin
+[[autodoc]] TFGenerationMixin
 	- generate
 	- compute_transition_scores
 
 ## FlaxGenerationMixin
 
-[[autodoc]] generation.FlaxGenerationMixin
+[[autodoc]] FlaxGenerationMixin
 	- generate
diff --git a/src/transformers/integrations/executorch.py b/src/transformers/integrations/executorch.py
index c0adff386f6..258017f1418 100644
--- a/src/transformers/integrations/executorch.py
+++ b/src/transformers/integrations/executorch.py
@@ -12,11 +12,15 @@
 
 import torch
 
-from transformers import (
-    PreTrainedModel,
-    StaticCache,
-)
-from transformers.pytorch_utils import is_torch_greater_or_equal_than_2_3
+from ..utils.import_utils import is_torch_available
+
+
+if is_torch_available():
+    from transformers import (
+        PreTrainedModel,
+        StaticCache,
+    )
+    from transformers.pytorch_utils import is_torch_greater_or_equal_than_2_3
 
 
 class TorchExportableModuleWithStaticCache(torch.nn.Module):
diff --git a/src/transformers/utils/import_utils.py b/src/transformers/utils/import_utils.py
index 519755489a3..fbc248824a4 100755
--- a/src/transformers/utils/import_utils.py
+++ b/src/transformers/utils/import_utils.py
@@ -1751,9 +1751,7 @@ class _LazyModule(ModuleType):
     def __getattr__(self, name: str) -> Any:
         if name in self._objects:
             return self._objects[name]
-        if name in self._modules:
-            value = self._get_module(name)
-        elif name in self._object_missing_backend.keys():
+        if name in self._object_missing_backend.keys():
             missing_backends = self._object_missing_backend[name]
 
             class Placeholder(metaclass=DummyObject):
@@ -1769,6 +1767,8 @@ class _LazyModule(ModuleType):
         elif name in self._class_to_module.keys():
             module = self._get_module(self._class_to_module[name])
             value = getattr(module, name)
+        elif name in self._modules:
+            value = self._get_module(name)
         else:
             raise AttributeError(f"module {self.__name__} has no attribute {name}")
 
diff --git a/utils/check_repo.py b/utils/check_repo.py
index 3ecbd79eca4..98f96bcc78a 100644
--- a/utils/check_repo.py
+++ b/utils/check_repo.py
@@ -1089,18 +1089,34 @@ def check_public_method_exists(documented_methods_map):
             for submodule_name in nested_submodules:
                 if submodule_name == "transformers":
                     continue
-                submodule = getattr(submodule, submodule_name)
+
+                try:
+                    submodule = getattr(submodule, submodule_name)
+                except AttributeError:
+                    failures.append(f"Could not parse {submodule_name}. Are the required dependencies installed?")
+                continue
+
         class_name = nested_path[-1]
-        obj_class = getattr(submodule, class_name)
+
+        try:
+            obj_class = getattr(submodule, class_name)
+        except AttributeError:
+            failures.append(f"Could not parse {submodule_name}. Are the required dependencies installed?")
+            continue
+
         # Checks that all explicitly documented methods are defined in the class
         for method in methods:
             if method == "all":  # Special keyword to document all public methods
                 continue
-            if not hasattr(obj_class, method):
-                failures.append(
-                    "The following public method is explicitly documented but not defined in the corresponding "
-                    f"class. class: {obj}, method: {method}"
-                )
+            try:
+                if not hasattr(obj_class, method):
+                    failures.append(
+                        "The following public method is explicitly documented but not defined in the corresponding "
+                        f"class. class: {obj}, method: {method}. If the method is defined, this error can be due to "
+                        f"lacking dependencies."
+                    )
+            except ImportError:
+                pass
 
     if len(failures) > 0:
         raise Exception("\n".join(failures))