try fp16

app.py

@@ -24,8 +24,8 @@ def hf_hub_download_local(repo_id, filename, local_dir, **kwargs):
 print("Downloading models from Hugging Face Hub...")
 text_encoder_repo = hf_hub_download_local(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors", local_dir="models/text_encoders")
 print(text_encoder_repo)
-hf_hub_download_local(repo_id="Comfy-Org/Wan_2.2_ComfyUI_Repackaged", filename="split_files/diffusion_models/wan2.2_i2v_low_noise_14B_fp8_scaled.safetensors", local_dir="models/unet")
-hf_hub_download_local(repo_id="Comfy-Org/Wan_2.2_ComfyUI_Repackaged", filename="split_files/diffusion_models/wan2.2_i2v_high_noise_14B_fp8_scaled.safetensors", local_dir="models/unet")
+hf_hub_download_local(repo_id="Comfy-Org/Wan_2.2_ComfyUI_Repackaged", filename="split_files/diffusion_models/wan2.2_i2v_low_noise_14B_fp16.safetensors", local_dir="models/unet")
+hf_hub_download_local(repo_id="Comfy-Org/Wan_2.2_ComfyUI_Repackaged", filename="split_files/diffusion_models/wan2.2_i2v_high_noise_14B_fp16.safetensors", local_dir="models/unet")
 hf_hub_download_local(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/vae/wan_2.1_vae.safetensors", local_dir="models/vae")
 hf_hub_download_local(repo_id="Comfy-Org/Wan_2.1_ComfyUI_repackaged", filename="split_files/clip_vision/clip_vision_h.safetensors", local_dir="models/clip_vision")
 hf_hub_download_local(repo_id="Kijai/WanVideo_comfy", filename="Wan22-Lightning/Wan2.2-Lightning_I2V-A14B-4steps-lora_HIGH_fp16.safetensors", local_dir="models/loras")
@@ -78,8 +78,8 @@ createvideo = nodes.NODE_CLASS_MAPPINGS["CreateVideo"]()
 savevideo = nodes.NODE_CLASS_MAPPINGS["SaveVideo"]()
 
 cliploader_38 = cliploader.load_clip(clip_name="umt5_xxl_fp8_e4m3fn_scaled.safetensors", type="wan", device="cpu")
-unetloader_37_low_noise = unetloader.load_unet(unet_name="wan2.2_i2v_low_noise_14B_fp8_scaled.safetensors", weight_dtype="default")
-unetloader_91_high_noise = unetloader.load_unet(unet_name="wan2.2_i2v_high_noise_14B_fp8_scaled.safetensors", weight_dtype="default")
+unetloader_37_low_noise = unetloader.load_unet(unet_name="wan2.2_i2v_low_noise_14B_fp16.safetensors", weight_dtype="default")
+unetloader_91_high_noise = unetloader.load_unet(unet_name="wan2.2_i2v_high_noise_14B_fp16.safetensors", weight_dtype="default")
 vaeloader_39 = vaeloader.load_vae(vae_name="wan_2.1_vae.safetensors")
 clipvisionloader_49 = clipvisionloader.load_clip(clip_name="clip_vision_h.safetensors")
 
@@ -92,6 +92,7 @@ pathchsageattentionkj_96_high = pathchsageattentionkj.patch(sage_attention="auto
 
 model_loaders = [cliploader_38, unetloader_37_low_noise, unetloader_91_high_noise, vaeloader_39, clipvisionloader_49, loraloadermodelonly_94_high, loraloadermodelonly_95_low]
 valid_models = [getattr(loader[0], 'patcher', loader[0]) for loader in model_loaders if not isinstance(loader[0], dict) and not isinstance(getattr(loader[0], 'patcher', None), dict)]
+model_management.load_models_gpu(valid_models)
 
 # --- App Logic ---
 def calculate_dimensions(width, height):
@@ -107,7 +108,7 @@ def generate_video(prompt, first_image_path, last_image_path, duration_seconds):
     os.makedirs(temp_dir, exist_ok=True)
     
     with torch.inference_mode():
-        model_management.load_models_gpu(valid_models)
+        
         # --- Python Image Preprocessing using Pillow ---
         print("Preprocessing images with Pillow...")
         with Image.open(first_image_path) as img: