diff --git a/extensions-builtin/Lora/network_lora.py b/extensions-builtin/Lora/network_lora.py
index 7dfded536..da4f6645f 100644
--- a/extensions-builtin/Lora/network_lora.py
+++ b/extensions-builtin/Lora/network_lora.py
@@ -27,7 +27,7 @@ def create_module(self, weights, key, none_ok=False):
         if weight is None and none_ok:
             return None
         linear_modules = [torch.nn.Linear, torch.nn.modules.linear.NonDynamicallyQuantizableLinear, torch.nn.MultiheadAttention, diffusers_lora.LoRACompatibleLinear]
-        is_linear = type(self.sd_module) in linear_modules or self.sd_module.__class__.__name__ in {"NNCFLinear", "QLinear"}
+        is_linear = type(self.sd_module) in linear_modules or self.sd_module.__class__.__name__ in {"NNCFLinear", "QLinear", "Linear4bit"}
         is_conv = type(self.sd_module) in [torch.nn.Conv2d, diffusers_lora.LoRACompatibleConv] or self.sd_module.__class__.__name__ in {"NNCFConv2d", "QConv2d"}
         if is_linear:
             weight = weight.reshape(weight.shape[0], -1)
diff --git a/extensions-builtin/Lora/network_overrides.py b/extensions-builtin/Lora/network_overrides.py
index 9123d0039..24afb0c28 100644
--- a/extensions-builtin/Lora/network_overrides.py
+++ b/extensions-builtin/Lora/network_overrides.py
@@ -30,7 +30,6 @@
     'kandinsky',
     'hunyuandit',
     'auraflow',
-    'f1',
 ]
 
 force_classes = [ # forced always
diff --git a/extensions-builtin/Lora/networks.py b/extensions-builtin/Lora/networks.py
index 6e20b5a59..fdbfd3401 100644
--- a/extensions-builtin/Lora/networks.py
+++ b/extensions-builtin/Lora/networks.py
@@ -50,23 +50,29 @@
 def assign_network_names_to_compvis_modules(sd_model):
     network_layer_mapping = {}
     if shared.native:
-        if not hasattr(shared.sd_model, 'text_encoder') or not hasattr(shared.sd_model, 'unet'):
-            sd_model.network_layer_mapping = {}
-            return
-        for name, module in shared.sd_model.text_encoder.named_modules():
-            prefix = "lora_te1_" if shared.sd_model_type == "sdxl" else "lora_te_"
-            network_name = prefix + name.replace(".", "_")
-            network_layer_mapping[network_name] = module
-            module.network_layer_name = network_name
-        if shared.sd_model_type == "sdxl":
+        if hasattr(shared.sd_model, 'text_encoder'):
+            for name, module in shared.sd_model.text_encoder.named_modules():
+                prefix = "lora_te1_" if hasattr(shared.sd_model, 'text_encoder_2') else "lora_te_"
+                network_name = prefix + name.replace(".", "_")
+                network_layer_mapping[network_name] = module
+                module.network_layer_name = network_name
+        if hasattr(shared.sd_model, 'text_encoder_2'):
             for name, module in shared.sd_model.text_encoder_2.named_modules():
                 network_name = "lora_te2_" + name.replace(".", "_")
                 network_layer_mapping[network_name] = module
                 module.network_layer_name = network_name
-        for name, module in shared.sd_model.unet.named_modules():
-            network_name = "lora_unet_" + name.replace(".", "_")
-            network_layer_mapping[network_name] = module
-            module.network_layer_name = network_name
+        if hasattr(shared.sd_model, 'unet'):
+            for name, module in shared.sd_model.unet.named_modules():
+                network_name = "lora_unet_" + name.replace(".", "_")
+                network_layer_mapping[network_name] = module
+                module.network_layer_name = network_name
+        if hasattr(shared.sd_model, 'transformer'):
+            for name, module in shared.sd_model.transformer.named_modules():
+                network_name = "lora_transformer_" + name.replace(".", "_")
+                network_layer_mapping[network_name] = module
+                if "norm" in network_name and "linear" not in network_name:
+                    continue
+                module.network_layer_name = network_name
     else:
         if not hasattr(shared.sd_model, 'cond_stage_model'):
             sd_model.network_layer_mapping = {}