diff --git a/modules/sd_disable_initialization.py b/modules/sd_disable_initialization.py
index 088ac24b..c72d8efc 100644
--- a/modules/sd_disable_initialization.py
+++ b/modules/sd_disable_initialization.py
@@ -20,6 +20,19 @@ class DisableInitialization:
     ```
     """
 
+    def __init__(self):
+        self.replaced = []
+
+    def replace(self, obj, field, func):
+        original = getattr(obj, field, None)
+        if original is None:
+            return None
+
+        self.replaced.append((obj, field, original))
+        setattr(obj, field, func)
+
+        return original
+
     def __enter__(self):
         def do_nothing(*args, **kwargs):
             pass
@@ -37,11 +50,14 @@ class DisableInitialization:
         def transformers_utils_hub_get_file_from_cache(original, url, *args, **kwargs):
 
             # this file is always 404, prevent making request
-            if url == 'https://huggingface.co/openai/clip-vit-large-patch14/resolve/main/added_tokens.json':
-                raise transformers.utils.hub.EntryNotFoundError
+            if url == 'https://huggingface.co/openai/clip-vit-large-patch14/resolve/main/added_tokens.json' or url == 'openai/clip-vit-large-patch14' and args[0] == 'added_tokens.json':
+                return None
 
             try:
-                return original(url, *args, local_files_only=True, **kwargs)
+                res = original(url, *args, local_files_only=True, **kwargs)
+                if res is None:
+                    res = original(url, *args, local_files_only=False, **kwargs)
+                return res
             except Exception as e:
                 return original(url, *args, local_files_only=False, **kwargs)
 
@@ -54,42 +70,19 @@ class DisableInitialization:
         def transformers_configuration_utils_cached_file(url, *args, local_files_only=False, **kwargs):
             return transformers_utils_hub_get_file_from_cache(self.transformers_configuration_utils_cached_file, url, *args, **kwargs)
 
-        self.init_kaiming_uniform = torch.nn.init.kaiming_uniform_
-        self.init_no_grad_normal = torch.nn.init._no_grad_normal_
-        self.init_no_grad_uniform_ = torch.nn.init._no_grad_uniform_
-        self.create_model_and_transforms = open_clip.create_model_and_transforms
-        self.CLIPTextModel_from_pretrained = ldm.modules.encoders.modules.CLIPTextModel.from_pretrained
-        self.transformers_modeling_utils_load_pretrained_model = getattr(transformers.modeling_utils.PreTrainedModel, '_load_pretrained_model', None)
-        self.transformers_tokenization_utils_base_cached_file = getattr(transformers.tokenization_utils_base, 'cached_file', None)
-        self.transformers_configuration_utils_cached_file = getattr(transformers.configuration_utils, 'cached_file', None)
-        self.transformers_utils_hub_get_from_cache = getattr(transformers.utils.hub, 'get_from_cache', None)
-
-        torch.nn.init.kaiming_uniform_ = do_nothing
-        torch.nn.init._no_grad_normal_ = do_nothing
-        torch.nn.init._no_grad_uniform_ = do_nothing
-        open_clip.create_model_and_transforms = create_model_and_transforms_without_pretrained
-        ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = CLIPTextModel_from_pretrained
-        if self.transformers_modeling_utils_load_pretrained_model is not None:
-            transformers.modeling_utils.PreTrainedModel._load_pretrained_model = transformers_modeling_utils_load_pretrained_model
-        if self.transformers_tokenization_utils_base_cached_file is not None:
-            transformers.tokenization_utils_base.cached_file = transformers_tokenization_utils_base_cached_file
-        if self.transformers_configuration_utils_cached_file is not None:
-            transformers.configuration_utils.cached_file = transformers_configuration_utils_cached_file
-        if self.transformers_utils_hub_get_from_cache is not None:
-            transformers.utils.hub.get_from_cache = transformers_utils_hub_get_from_cache
+        self.replace(torch.nn.init, 'kaiming_uniform_', do_nothing)
+        self.replace(torch.nn.init, '_no_grad_normal_', do_nothing)
+        self.replace(torch.nn.init, '_no_grad_uniform_', do_nothing)
+        self.create_model_and_transforms = self.replace(open_clip, 'create_model_and_transforms', create_model_and_transforms_without_pretrained)
+        self.CLIPTextModel_from_pretrained = self.replace(ldm.modules.encoders.modules.CLIPTextModel, 'from_pretrained', CLIPTextModel_from_pretrained)
+        self.transformers_modeling_utils_load_pretrained_model = self.replace(transformers.modeling_utils.PreTrainedModel, '_load_pretrained_model', transformers_modeling_utils_load_pretrained_model)
+        self.transformers_tokenization_utils_base_cached_file = self.replace(transformers.tokenization_utils_base, 'cached_file', transformers_tokenization_utils_base_cached_file)
+        self.transformers_configuration_utils_cached_file = self.replace(transformers.configuration_utils, 'cached_file', transformers_configuration_utils_cached_file)
+        self.transformers_utils_hub_get_from_cache = self.replace(transformers.utils.hub, 'get_from_cache', transformers_utils_hub_get_from_cache)
 
     def __exit__(self, exc_type, exc_val, exc_tb):
-        torch.nn.init.kaiming_uniform_ = self.init_kaiming_uniform
-        torch.nn.init._no_grad_normal_ = self.init_no_grad_normal
-        torch.nn.init._no_grad_uniform_ = self.init_no_grad_uniform_
-        open_clip.create_model_and_transforms = self.create_model_and_transforms
-        ldm.modules.encoders.modules.CLIPTextModel.from_pretrained = self.CLIPTextModel_from_pretrained
-        if self.transformers_modeling_utils_load_pretrained_model is not None:
-            transformers.modeling_utils.PreTrainedModel._load_pretrained_model = self.transformers_modeling_utils_load_pretrained_model
-        if self.transformers_tokenization_utils_base_cached_file is not None:
-            transformers.utils.hub.cached_file = self.transformers_tokenization_utils_base_cached_file
-        if self.transformers_configuration_utils_cached_file is not None:
-            transformers.utils.hub.cached_file = self.transformers_configuration_utils_cached_file
-        if self.transformers_utils_hub_get_from_cache is not None:
-            transformers.utils.hub.get_from_cache = self.transformers_utils_hub_get_from_cache
+        for obj, field, original in self.replaced:
+            setattr(obj, field, original)
+
+        self.replaced.clear()
 
diff --git a/modules/sd_models.py b/modules/sd_models.py
index 084ba7fa..c466f273 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -334,6 +334,7 @@ def load_model(checkpoint_info=None):
     timer = Timer()
 
     sd_model = None
+
     try:
         with sd_disable_initialization.DisableInitialization():
             sd_model = instantiate_from_config(sd_config.model)