diff --git a/node.py b/node.py
index 0afd2c4..b6a1d73 100644
--- a/node.py
+++ b/node.py
@@ -20,17 +20,19 @@ class Eden_LoRa_trainer:
             "required": {
                     "training_images_folder_path": ("STRING", {"default": "."}),
                     "ckpt_name": (folder_paths.get_filename_list("checkpoints"), ),
-                    "lora_name": ("STRING", {"default": "Eden_LoRa"}),
+                    "lora_name": ("STRING", {"default": "Eden_Token_LoRa"}),
                     "mode": (["style", "face", "object"], ),
+                    "training_resolution": ("INT", {"default": 512, "min": 256, "max": 1024}),
                     "train_batch_size": ("INT", {"default": 4, "min": 1, "max": 8}),
-                    "max_train_steps":  ("INT", {"default": 360, "min": 10, "max": 10000}),
-                    "ti_lr":   ("FLOAT", {"default": 0.001, "min": 0.0001, "max": 0.01, "step": 0.0001}),
-                    "unet_lr": ("FLOAT", {"default": 0.001, "min": 0.0001, "max": 0.01, "step": 0.0001}),
+                    "max_train_steps":  ("INT", {"default": 300, "min": 10, "max": 10000}),
+                    "ti_lr":   ("FLOAT", {"default": 0.001, "min": 0.0, "max": 0.005, "step": 0.0001}),
+                    "unet_lr": ("FLOAT", {"default": 0.0005, "min": 0.0, "max": 0.005, "step": 0.0001}),
                     "lora_rank": ("INT", {"default": 16, "min": 1, "max": 64}),
                     "disable_ti": ("BOOLEAN", {"default": False}),
                     "n_tokens": ("INT", {"default": 3, "min": 1, "max": 5}),
                     "debug_mode": ("BOOLEAN", {"default": False}),
-                    "save_checkpoint_every_n_steps": ("INT", {"default": 180, "min": 10, "max": 10000}),
+                    "save_checkpoint_every_n_steps": ("INT", {"default": 200, "min": 10, "max": 10000}),
+                    "sample_imgs_lora_scale": ("FLOAT", {"default": 0.7, "min": 0.0, "max": 1.25}),
                     "seed": ("INT", {"default": 0, "min": 0, "max": 100000}),
                 }
         }
@@ -43,24 +45,27 @@ class Eden_LoRa_trainer:
     def train_lora(self, 
             training_images_folder_path,
             ckpt_name,
-            lora_name = "eden_lora",
-            mode = "style",
-            seed = 0,
-            train_batch_size = 4,
-            max_train_steps = 360,
-            ti_lr = 0.001,
-            unet_lr = 0.001,
-            lora_rank = 16,
-            disable_ti = False,
-            n_tokens = 3,
-            debug_mode = False,
-            save_checkpoint_every_n_steps = 180,
+            lora_name,
+            mode,
+            training_resolution,
+            train_batch_size,
+            max_train_steps ,
+            ti_lr,
+            unet_lr,
+            lora_rank,
+            disable_ti,
+            n_tokens,
+            debug_mode,
+            save_checkpoint_every_n_steps,
+            sample_imgs_lora_scale,
+            seed,
             ):
         
         print("Starting new training job...")
 
         # Overwrite hardcoded paths to point to comfyUI folders:
         model_paths.set_path("CLIP", os.path.join(folder_paths.models_dir, "clipseg"))
+        model_paths.set_path("FLORENCE", os.path.join(folder_paths.models_dir, "LLM"))
         model_paths.set_path("BLIP", os.path.join(folder_paths.models_dir, "blip"))
         model_paths.set_path("SR", os.path.join(folder_paths.models_dir, "upscale_models"))
         model_paths.set_path("SD", os.path.join(folder_paths.models_dir, "checkpoints"))
@@ -74,10 +79,11 @@ class Eden_LoRa_trainer:
             concept_mode=mode,
             ckpt_path=ckpt_path,
             seed=seed,
-            resolution=512,
+            resolution=training_resolution,
             train_batch_size=train_batch_size,
             max_train_steps=max_train_steps,
             checkpointing_steps=save_checkpoint_every_n_steps,
+            sample_imgs_lora_scale=sample_imgs_lora_scale,
             ti_lr=ti_lr,
             unet_lr=unet_lr,
             lora_rank=lora_rank,