diff --git a/fooocus_version.py b/fooocus_version.py
index 00b3f850..2cfedeae 100644
--- a/fooocus_version.py
+++ b/fooocus_version.py
@@ -1 +1 @@
-version = '2.1.48'
+version = '2.1.49'
diff --git a/modules/core.py b/modules/core.py
index b49189a2..42a8a2b9 100644
--- a/modules/core.py
+++ b/modules/core.py
@@ -197,7 +197,9 @@ def get_previewer():
 @torch.inference_mode()
 def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sampler_name='dpmpp_fooocus_2m_sde_inpaint_seamless',
              scheduler='karras', denoise=1.0, disable_noise=False, start_step=None, last_step=None,
-             force_full_denoise=False, callback_function=None, refiner=None, refiner_switch=-1, previewer_start=None, previewer_end=None):
+             force_full_denoise=False, callback_function=None, refiner=None, refiner_switch=-1,
+             previewer_start=None, previewer_end=None, noise_multiplier=1.0):
+
     latent_image = latent["samples"]
     if disable_noise:
         noise = torch.zeros(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, device="cpu")
@@ -205,6 +207,9 @@ def ksampler(model, positive, negative, latent, seed=None, steps=30, cfg=7.0, sa
         batch_inds = latent["batch_index"] if "batch_index" in latent else None
         noise = comfy.sample.prepare_noise(latent_image, seed, batch_inds)
 
+    if noise_multiplier != 1.0:
+        noise = noise * noise_multiplier
+
     noise_mask = None
     if "noise_mask" in latent:
         noise_mask = latent["noise_mask"]
diff --git a/modules/default_pipeline.py b/modules/default_pipeline.py
index 534b2c88..c2cc54da 100644
--- a/modules/default_pipeline.py
+++ b/modules/default_pipeline.py
@@ -123,7 +123,7 @@ def refresh_refiner_model(name):
         xl_refiner.clip = None
         xl_refiner.vae = None
     else:
-        xl_refiner = None  # 1.5/2.1 not supported yet.
+        xl_refiner.clip = None
 
     return
 
@@ -387,6 +387,7 @@ def process_diffusion(positive_cond, negative_cond, steps, switch, width, height
             scheduler=scheduler_name,
             previewer_start=switch,
             previewer_end=steps,
+            noise_multiplier=1.2,
         )
 
         target_model = final_refiner_vae