diff --git a/jobs/process/BaseSDTrainProcess.py b/jobs/process/BaseSDTrainProcess.py
index 50d415af..9b3a5b5c 100644
--- a/jobs/process/BaseSDTrainProcess.py
+++ b/jobs/process/BaseSDTrainProcess.py
@@ -722,7 +722,9 @@ class BaseSDTrainProcess(BaseTrainProcess):
                     conv_alpha=self.network_config.conv_alpha,
                     is_sdxl=self.model_config.is_xl,
                     is_v2=self.model_config.is_v2,
-                    dropout=self.network_config.dropout
+                    dropout=self.network_config.dropout,
+                    use_text_encoder_1=self.model_config.use_text_encoder_1,
+                    use_text_encoder_2=self.model_config.use_text_encoder_2,
                 )
 
                 self.network.force_to(self.device_torch, dtype=dtype)
diff --git a/toolkit/lora_special.py b/toolkit/lora_special.py
index aadaf541..5e599227 100644
--- a/toolkit/lora_special.py
+++ b/toolkit/lora_special.py
@@ -137,6 +137,8 @@ class LoRASpecialNetwork(ToolkitNetworkMixin, LoRANetwork):
             module_class: Type[object] = LoRAModule,
             varbose: Optional[bool] = False,
             train_text_encoder: Optional[bool] = True,
+            use_text_encoder_1: bool = True,
+            use_text_encoder_2: bool = True,
             train_unet: Optional[bool] = True,
             is_sdxl=False,
             is_v2=False,
@@ -273,6 +275,10 @@ class LoRASpecialNetwork(ToolkitNetworkMixin, LoRANetwork):
         skipped_te = []
         if train_text_encoder:
             for i, text_encoder in enumerate(text_encoders):
+                if not use_text_encoder_1 and i == 0:
+                    continue
+                if not use_text_encoder_2 and i == 1:
+                    continue
                 if len(text_encoders) > 1:
                     index = i + 1
                     print(f"create LoRA for Text Encoder {index}:")
diff --git a/toolkit/lycoris_special.py b/toolkit/lycoris_special.py
index 36cdd8b7..d007de6c 100644
--- a/toolkit/lycoris_special.py
+++ b/toolkit/lycoris_special.py
@@ -156,6 +156,8 @@ class LycorisSpecialNetwork(ToolkitNetworkMixin, LycorisNetwork):
             network_module: Type[object] = LoConSpecialModule,
             train_unet: bool = True,
             train_text_encoder: bool = True,
+            use_text_encoder_1: bool = True,
+            use_text_encoder_2: bool = True,
             **kwargs,
     ) -> None:
         # call ToolkitNetworkMixin super
@@ -332,6 +334,10 @@ class LycorisSpecialNetwork(ToolkitNetworkMixin, LycorisNetwork):
         self.text_encoder_loras = []
         if self.train_text_encoder:
             for i, te in enumerate(text_encoders):
+                if not use_text_encoder_1 and i == 0:
+                    continue
+                if not use_text_encoder_2 and i == 1:
+                    continue
                 self.text_encoder_loras.extend(create_modules(
                     LycorisSpecialNetwork.LORA_PREFIX_TEXT_ENCODER + (f'{i + 1}' if use_index else ''),
                     te,
diff --git a/toolkit/sd_device_states_presets.py b/toolkit/sd_device_states_presets.py
index fc16fd9e..3cf78017 100644
--- a/toolkit/sd_device_states_presets.py
+++ b/toolkit/sd_device_states_presets.py
@@ -60,7 +60,7 @@ def get_train_sd_device_state_preset(
         preset['unet']['training'] = True
 
     if train_lora:
-        preset['text_encoder']['requires_grad'] = False
+        # preset['text_encoder']['requires_grad'] = False
         preset['unet']['requires_grad'] = False
 
     if train_adapter:
diff --git a/toolkit/stable_diffusion_model.py b/toolkit/stable_diffusion_model.py
index f1959beb..8d3ae4c4 100644
--- a/toolkit/stable_diffusion_model.py
+++ b/toolkit/stable_diffusion_model.py
@@ -1,6 +1,7 @@
 import copy
 import gc
 import json
+import random
 import shutil
 import typing
 from typing import Union, List, Literal, Iterator
@@ -677,6 +678,14 @@ class StableDiffusion:
         if prompt2 is not None and not isinstance(prompt2, list):
             prompt2 = [prompt2]
         if self.is_xl:
+            # todo make this a config
+            # 50% chance to use an encoder anyway even if it is disabled
+            # allows the other TE to compensate for the disabled one
+            use_encoder_1 = self.use_text_encoder_1 or force_all or random.random() > 0.5
+            use_encoder_2 = self.use_text_encoder_2 or force_all or random.random() > 0.5
+            # use_encoder_1 = True
+            # use_encoder_2 = True
+
             return PromptEmbeds(
                 train_tools.encode_prompts_xl(
                     self.tokenizer,
@@ -684,8 +693,8 @@ class StableDiffusion:
                     prompt,
                     prompt2,
                     num_images_per_prompt=num_images_per_prompt,
-                    use_text_encoder_1=self.use_text_encoder_1 or force_all,
-                    use_text_encoder_2=self.use_text_encoder_2 or force_all,
+                    use_text_encoder_1=use_encoder_1,
+                    use_text_encoder_2=use_encoder_2,
                 )
             )
         else:
@@ -831,6 +840,13 @@ class StableDiffusion:
         if text_encoder:
             if isinstance(self.text_encoder, list):
                 for i, encoder in enumerate(self.text_encoder):
+                    if self.is_xl and not self.model_config.use_text_encoder_1 and i == 0:
+                        # dont add these params
+                        continue
+                    if self.is_xl and not self.model_config.use_text_encoder_2 and i == 1:
+                        # dont add these params
+                        continue
+
                     for name, param in encoder.named_parameters(recurse=True, prefix=f"{SD_PREFIX_TEXT_ENCODER}{i}"):
                         named_params[name] = param
             else: