diff --git a/fooocus_version.py b/fooocus_version.py
index 090441a..c7df6d4 100644
--- a/fooocus_version.py
+++ b/fooocus_version.py
@@ -1 +1 @@
-version = '2.0.90'
+version = '2.0.91'
diff --git a/modules/async_worker.py b/modules/async_worker.py
index 2b3b17d..45a906a 100644
--- a/modules/async_worker.py
+++ b/modules/async_worker.py
@@ -48,7 +48,7 @@ def worker():
         execution_start_time = time.perf_counter()
 
         prompt, negative_prompt, style_selections, performance_selection, \
-            aspect_ratios_selection, image_number, image_seed, sharpness, adm_scaler_positive, adm_scaler_negative, guidance_scale, adaptive_cfg, sampler_name, scheduler_name, \
+            aspect_ratios_selection, image_number, image_seed, sharpness, adm_scaler_positive, adm_scaler_negative, adm_scaler_end, guidance_scale, adaptive_cfg, sampler_name, scheduler_name, \
             overwrite_step, overwrite_switch, overwrite_width, overwrite_height, overwrite_vary_strength, overwrite_upscale_strength, \
             base_model_name, refiner_model_name, \
             l1, w1, l2, w2, l3, w3, l4, w4, l5, w5, \
@@ -80,7 +80,8 @@ def worker():
 
         modules.patch.positive_adm_scale = adm_scaler_positive
         modules.patch.negative_adm_scale = adm_scaler_negative
-        print(f'[Parameters] ADM Scale = {modules.patch.positive_adm_scale} / {modules.patch.negative_adm_scale}')
+        modules.patch.adm_scaler_end = adm_scaler_end
+        print(f'[Parameters] ADM Scale = {modules.patch.positive_adm_scale} : {modules.patch.negative_adm_scale} : {modules.patch.adm_scaler_end}')
 
         cfg_scale = float(guidance_scale)
         print(f'[Parameters] CFG = {cfg_scale}')
diff --git a/modules/patch.py b/modules/patch.py
index 7a41c9e..32e7a25 100644
--- a/modules/patch.py
+++ b/modules/patch.py
@@ -20,6 +20,8 @@ from comfy.ldm.modules.diffusionmodules.openaimodel import timestep_embedding, f
 
 
 sharpness = 2.0
+
+adm_scaler_end = 0.3
 positive_adm_scale = 1.5
 negative_adm_scale = 0.8
 
@@ -340,10 +342,10 @@ def patched_unet_forward(self, x, timesteps=None, context=None, y=None, control=
     transformer_patches = transformer_options.get("patches", {})
 
     if isinstance(y, torch.Tensor) and int(y.dim()) == 2 and int(y.shape[1]) == 5632:
-        t = (timesteps / 999.0)[:, None].clone().to(x) ** 2.0
-        ya = y[..., :2816].clone()
-        yb = y[..., 2816:].clone()
-        y = t * ya + (1 - t) * yb
+        y_mask = (timesteps > 999.0 * (1.0 - float(adm_scaler_end))).to(y)[..., None]
+        y_with_adm = y[..., :2816].clone()
+        y_without_adm = y[..., 2816:].clone()
+        y = y_with_adm * y_mask + y_without_adm * (1.0 - y_mask)
 
     hs = []
     t_emb = timestep_embedding(timesteps, self.model_channels, repeat_only=False).to(self.dtype)
diff --git a/webui.py b/webui.py
index d6e7402..1bf2509 100644
--- a/webui.py
+++ b/webui.py
@@ -165,6 +165,9 @@ with shared.gradio_root:
                                                         step=0.001, value=1.5, info='The scaler multiplied to positive ADM (use 1.0 to disable). ')
                         adm_scaler_negative = gr.Slider(label='Negative ADM Guidance Scaler', minimum=0.1, maximum=3.0,
                                                         step=0.001, value=0.8, info='The scaler multiplied to negative ADM (use 1.0 to disable). ')
+                        adm_scaler_end = gr.Slider(label='ADM Guidance End At Step', minimum=0.0, maximum=1.0,
+                                                   step=0.001, value=0.3,
+                                                   info='When to end the guidance from positive/negative ADM. ')
                         adaptive_cfg = gr.Slider(label='CFG Mimicking from TSNR', minimum=1.0, maximum=30.0, step=0.01, value=7.0,
                                                  info='Enabling Fooocus\'s implementation of CFG mimicking for TSNR '
                                                       '(effective when real CFG > mimicked CFG).')
@@ -211,7 +214,7 @@ with shared.gradio_root:
         advanced_checkbox.change(lambda x: gr.update(visible=x), advanced_checkbox, right_col, queue=False)
         ctrls = [
             prompt, negative_prompt, style_selections,
-            performance_selection, aspect_ratios_selection, image_number, image_seed, sharpness, adm_scaler_positive, adm_scaler_negative, guidance_scale, adaptive_cfg, sampler_name, scheduler_name
+            performance_selection, aspect_ratios_selection, image_number, image_seed, sharpness, adm_scaler_positive, adm_scaler_negative, adm_scaler_end, guidance_scale, adaptive_cfg, sampler_name, scheduler_name
         ]
         ctrls += overwrite_ctrls
         ctrls += [base_model, refiner_model] + lora_ctrls