diff --git a/jobs/process/BaseSDTrainProcess.py b/jobs/process/BaseSDTrainProcess.py
index 276e72fc..e77db6a0 100644
--- a/jobs/process/BaseSDTrainProcess.py
+++ b/jobs/process/BaseSDTrainProcess.py
@@ -748,6 +748,8 @@ class BaseSDTrainProcess(BaseTrainProcess):
                 sig = inspect.signature(self.network.prepare_optimizer_params)
                 if 'default_lr' in sig.parameters:
                     config['default_lr'] = self.train_config.lr
+                if 'learning_rate' in sig.parameters:
+                    config['learning_rate'] = self.train_config.lr
                 params_net = self.network.prepare_optimizer_params(
                     **config
                 )
diff --git a/jobs/process/TrainSliderProcess.py b/jobs/process/TrainSliderProcess.py
index 180be04f..92f60925 100644
--- a/jobs/process/TrainSliderProcess.py
+++ b/jobs/process/TrainSliderProcess.py
@@ -216,9 +216,11 @@ class TrainSliderProcess(BaseSDTrainProcess):
             # called before LoRA network is loaded but after model is loaded
             # attach the adapter here so it is there before we load the network
             adapter_path = 'TencentARC/t2iadapter_depth_sd15v2'
-            if self.sd.is_xl:
+            if self.model_config.is_xl:
                 adapter_path = 'TencentARC/t2i-adapter-depth-midas-sdxl-1.0'
 
+            print(f"Loading T2I Adapter from {adapter_path}")
+
             # dont name this adapter since we are not training it
             self.t2i_adapter = T2IAdapter.from_pretrained(
                 adapter_path, torch_dtype=get_torch_dtype(self.train_config.dtype), varient="fp16"
diff --git a/requirements.txt b/requirements.txt
index 7bd2400f..5594e921 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,9 +1,9 @@
 torch
 torchvision
 safetensors
-diffusers==0.21.1
+diffusers==0.21.3
 transformers
-lycoris_lora
+lycoris-lora==1.8.3
 flatten_json
 pyyaml
 oyaml