diff --git a/nodes.py b/nodes.py
index c1ef9c2..ded96d9 100644
--- a/nodes.py
+++ b/nodes.py
@@ -712,7 +712,7 @@ class LoadWanVideoT5TextEncoder:
             },
             "optional": {
                 "load_device": (["main_device", "offload_device"], {"default": "offload_device"}),
-                 "quantization": (['disabled', 'fp8_e4m3fn'], {"default": 'disabled', "tooltip": "optional quantization method"}),
+                "quantization": (['disabled', 'fp8_e4m3fn'], {"default": 'disabled', "tooltip": "optional quantization method"}),
             }
         }
 
@@ -800,6 +800,7 @@ class WanVideoTextEncode:
             },
             "optional": {
                 "force_offload": ("BOOLEAN", {"default": True}),
+                "model_to_offload": ("WANVIDEOMODEL", {"tooltip": "Model to move to offload_device before encoding"}),
             }
         }
 
@@ -809,10 +810,16 @@ class WanVideoTextEncode:
     CATEGORY = "WanVideoWrapper"
     DESCRIPTION = "Encodes text prompts into text embeddings. For context windowing you can input multiple prompts separated by '|'"
 
-    def process(self, t5, positive_prompt, negative_prompt,force_offload=True):
+    def process(self, t5, positive_prompt, negative_prompt,force_offload=True, model_to_offload=None):
 
         device = mm.get_torch_device()
         offload_device = mm.unet_offload_device()
+
+        if model_to_offload is not None:
+            log.info(f"Moving video model to {offload_device}")
+            model_to_offload.model.to(offload_device)
+            mm.soft_empty_cache()
+
         encoder = t5["model"]
         dtype = t5["dtype"]
 
@@ -1682,8 +1689,12 @@ class WanVideoSampler:
                     if image_cond is not None:
                         partial_img_emb = image_cond[:, c, :, :]
                         partial_image_cond = image_cond[:, 0, :, :].to(intermediate_device)
-                        if min(c) > len(c) // 2:
-                            partial_image_cond *= 0.1
+                        if min(c) > 0: #wip
+                            control_strength = 1.0
+                            fade_rate = 0.01
+                            frame_position = min(c)
+                            strength = max(control_strength * (1.0 - (frame_position * fade_rate)), 0.1)
+                            partial_image_cond *= strength
                         partial_img_emb[:, 0, :, :] =  partial_image_cond
 
                     partial_latent_model_input = latent_model_input[:, c, :, :]