diff --git a/modules/impact/config.py b/modules/impact/config.py
index 6c29ab2..194c538 100644
--- a/modules/impact/config.py
+++ b/modules/impact/config.py
@@ -2,7 +2,7 @@ import configparser
 import os
 
 
-version_code = [4, 87]
+version_code = [4, 87, 1]
 version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
 
 dependency_version = 20
diff --git a/modules/thirdparty/noise_nodes.py b/modules/thirdparty/noise_nodes.py
index 39354d3..1e788c3 100644
--- a/modules/thirdparty/noise_nodes.py
+++ b/modules/thirdparty/noise_nodes.py
@@ -4,6 +4,8 @@
 
 import comfy
 import torch
+from comfy import sampler_helpers
+
 
 class Unsampler:
     @classmethod
@@ -39,7 +41,7 @@ class Unsampler:
         noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
         noise_mask = None
         if "noise_mask" in latent:
-            noise_mask = comfy.sample.prepare_mask(latent["noise_mask"], noise.shape, device)
+            noise_mask = comfy.sampler_helpers.prepare_mask(latent["noise_mask"], noise.shape, device)
 
         real_model = None
         real_model = model.model
@@ -47,17 +49,18 @@ class Unsampler:
         noise = noise.to(device)
         latent_image = latent_image.to(device)
 
-        positive = comfy.sample.convert_cond(positive)
-        negative = comfy.sample.convert_cond(negative)
+        positive = comfy.sampler_helpers.convert_cond(positive)
+        negative = comfy.sampler_helpers.convert_cond(negative)
 
-        models, inference_memory = comfy.sample.get_additional_models(positive, negative, model.model_dtype())
+        models1, inference_memory1 = comfy.sampler_helpers.get_additional_models(positive, model.model_dtype())
+        models2, inference_memory2 = comfy.sampler_helpers.get_additional_models(negative, model.model_dtype())
 
-        comfy.model_management.load_models_gpu([model] + models, model.memory_required(noise.shape) + inference_memory)
+        comfy.model_management.load_models_gpu([model] + models1 + models2, model.memory_required(noise.shape) + inference_memory1 + inference_memory2)
 
         sampler = comfy.samplers.KSampler(real_model, steps=steps, device=device, sampler=sampler_name,
                                           scheduler=scheduler, denoise=1.0, model_options=model.model_options)
 
-        sigmas = sigmas = sampler.sigmas.flip(0) + 0.0001
+        sigmas = sampler.sigmas.flip(0) + 0.0001
 
         pbar = comfy.utils.ProgressBar(steps)
 
@@ -73,7 +76,8 @@ class Unsampler:
             samples /= samples.std()
         samples = samples.cpu()
 
-        comfy.sample.cleanup_additional_models(models)
+        comfy.sampler_helpers.cleanup_additional_models(models1)
+        comfy.sampler_helpers.cleanup_additional_models(models2)
 
         out = latent.copy()
         out["samples"] = samples