diff --git a/modules/sd_models.py b/modules/sd_models.py
index f6cb2f34793b34535aa6915869d602584f50cbc7..a178adcacce1f9921f0458be7372834b2800a94d 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -640,8 +640,11 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer):
         timer.record("send model to device")
 
         model_data.set_sd_model(already_loaded)
-        shared.opts.data["sd_model_checkpoint"] = already_loaded.sd_checkpoint_info.title
-        shared.opts.data["sd_checkpoint_hash"] = already_loaded.sd_checkpoint_info.sha256
+
+        if not SkipWritingToConfig.skip:
+            shared.opts.data["sd_model_checkpoint"] = already_loaded.sd_checkpoint_info.title
+            shared.opts.data["sd_checkpoint_hash"] = already_loaded.sd_checkpoint_info.sha256
+
         print(f"Using already loaded model {already_loaded.sd_checkpoint_info.title}: done in {timer.summary()}")
         return model_data.sd_model
     elif shared.opts.sd_checkpoints_limit > 1 and len(model_data.loaded_sd_models) < shared.opts.sd_checkpoints_limit:
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index e1854980549a88d6eea3e45d5c673c2cfc891cc9..95a43ceff760e1fa472719c82930f6eb0d206e6a 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -1,8 +1,7 @@
 import torch
 import inspect
 import k_diffusion.sampling
-from modules import sd_samplers_common, sd_samplers_extra
-from modules.sd_samplers_cfg_denoiser import CFGDenoiser
+from modules import sd_samplers_common, sd_samplers_extra, sd_samplers_cfg_denoiser
 
 from modules.shared import opts
 import modules.shared as shared
diff --git a/modules/shared_options.py b/modules/shared_options.py
index 9ae51f1866df8cc4b4c520878c08a25f5db51f81..1e5b64eaf855e48086d24c6f25376e577d0175c7 100644
--- a/modules/shared_options.py
+++ b/modules/shared_options.py
@@ -140,6 +140,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
     "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"),
     "tiling": OptionInfo(False, "Tiling", infotext='Tiling').info("produce a tileable picture"),
+    "sd_refiner_checkpoint": OptionInfo("None", "Refiner checkpoint", gr.Dropdown, lambda: {"choices": ["None"] + shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints, infotext="Refiner").info("switch to another model in the middle of generation"),
+    "sd_refiner_switch_at": OptionInfo(1.0, "Refiner switch at", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Refiner switch at').info("fraction of sampling steps when the swtch to refiner model should happen; 1=never, 0.5=switch in the middle of generation"),
 }))
 
 options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), {