diff --git a/.eslintrc.json b/.eslintrc.json
index 6f7cf45d5..2bb10241b 100644
--- a/.eslintrc.json
+++ b/.eslintrc.json
@@ -2,7 +2,7 @@
   "parserOptions": {
     "ecmaVersion": 2020
   },
-  "plugins": ["html", "json", "markdown"],
+  "plugins": ["html", "json"],
   "extends": [
     "plugin:json/recommended",
     "eslint:recommended",
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 77cc9da9c..435f7559b 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -63,6 +63,11 @@ it is time to give credit to original [author](https://github.com/auTOMATIC1111)
     > --ipadapter 'Plus:~/generative/Samples/cutie-512.png:0.5'  
   - Add API endpoint `/sdapi/v1/vqa` and CLI util `cli/simple-vqa.py`
 - **Models**:
+  - **Load UNET**: ability to override/load external UNET to a selected model  
+    Works similar to how VAE is selected and loaded: Set UNet folder and UNet model in settings  
+    Can be replaced on-the-fly, not just during initial model load  
+    Enables usage of fine-tunes such as [DPO-SD15](https://huggingface.co/mhdang/dpo-sd1.5-text2image-v1) or [DPO-SDXL](https://huggingface.co/mhdang/dpo-sdxl-text2image-v1)  
+    *Note*: if there is a `JSON` file with the same name as the model it will be used as Unet config, otherwise Unet config from currently loaded model will be used  
   - [PixArt-Σ](https://pixart-alpha.github.io/PixArt-sigma-project/)
     pixart-Σ is a high end diffusion Transformer model (DiT) with a T5 encoder/decoder capable of directly generating images at 4K resolution  
     to use, simply select from *networks -> models -> PixArt-Σ*  
diff --git a/extensions-builtin/sdnext-modernui b/extensions-builtin/sdnext-modernui
index f789c7123..70822967d 160000
--- a/extensions-builtin/sdnext-modernui
+++ b/extensions-builtin/sdnext-modernui
@@ -1 +1 @@
-Subproject commit f789c7123871cf96fd161fb461709de76fea2087
+Subproject commit 70822967d57f89fc01304df4feb2b0e312047e17
diff --git a/javascript/black-teal.css b/javascript/black-teal.css
index 5632f0778..63f6fb5c4 100644
--- a/javascript/black-teal.css
+++ b/javascript/black-teal.css
@@ -54,11 +54,11 @@
   --line-md: 1.4em;
   --line-lg: 1.5em;
   --range-shadow:
-     -20em 0 0 0 hsl(180, 54%, 21%), -19em 0 0 0 hsl(180, 54%, 23%), -18em 0 0 0 hsl(180, 54%, 25%), -17em 0 0 0 hsl(180, 54%, 27%),
-     -16em 0 0 0 hsl(180, 54%, 29%), -15em 0 0 0 hsl(180, 54%, 31%), -14em 0 0 0 hsl(180, 54%, 33%), -13em 0 0 0 hsl(180, 54%, 35%),
-     -12em 0 0 0 hsl(180, 54%, 37%), -11em 0 0 0 hsl(180, 54%, 39%), -10em 0 0 0 hsl(180, 54%, 41%),  -9em 0 0 0 hsl(180, 54%, 43%),
-      -8em 0 0 0 hsl(180, 54%, 45%),  -7em 0 0 0 hsl(180, 54%, 47%), -6em 0 0 0 hsl(180, 54%, 49%),  -5em 0 0 0 hsl(180, 54%, 51%),
-      -4em 0 0 0 hsl(180, 54%, 53%),  -3em 0 0 0 hsl(180, 54%, 55%), -2em 0 0 0 hsl(180, 54%, 57%),  -1em 0 0 0 hsl(180, 54%, 59%),
+     -20em 0 0 0 hsl(180, 54%,  2%), -19em 0 0 0 hsl(180, 54%,  5%), -18em 0 0 0 hsl(180, 54%,  0%), -17em 0 0 0 hsl(180, 54%, 11%),
+     -16em 0 0 0 hsl(180, 54%, 14%), -15em 0 0 0 hsl(180, 54%, 17%), -14em 0 0 0 hsl(180, 54%, 20%), -13em 0 0 0 hsl(180, 54%, 23%),
+     -12em 0 0 0 hsl(180, 54%, 26%), -11em 0 0 0 hsl(180, 54%, 29%), -10em 0 0 0 hsl(180, 54%, 32%),  -9em 0 0 0 hsl(180, 54%, 35%),
+      -8em 0 0 0 hsl(180, 54%, 38%),  -7em 0 0 0 hsl(180, 54%, 41%), -6em 0 0 0 hsl(180, 54%, 44%),  -5em 0 0 0 hsl(180, 54%, 47%),
+      -4em 0 0 0 hsl(180, 54%, 50%),  -3em 0 0 0 hsl(180, 54%, 53%), -2em 0 0 0 hsl(180, 54%, 56%),  -1em 0 0 0 hsl(180, 54%, 59%),
       1em 0 0 0 var(--neutral-800),  2em 0 0 0 var(--neutral-800), 3em 0 0 0 var(--neutral-800),  4em 0 0 0 var(--neutral-800),
       5em 0 0 0 var(--neutral-800),  6em 0 0 0 var(--neutral-800), 7em 0 0 0 var(--neutral-800),  8em 0 0 0 var(--neutral-800),
       9em 0 0 0 var(--neutral-800), 10em 0 0 0 var(--neutral-800), 11em 0 0 0 var(--neutral-800), 12em 0 0 0 var(--neutral-800),
@@ -78,7 +78,7 @@ input[type=range]::-webkit-slider-thumb { border: 0px solid #000000 !important;
 input[type=range]::-moz-range-thumb     { border: 0px solid #000000 !important; height: var(--line-xs) !important; width: var(--line-md) !important; border-radius: var(--radius-lg) !important; background: var(--highlight-color) !important; cursor: pointer !important; appearance: none !important; margin-top: -4px !important; }
 */
 input[type='range'] { display: block; margin: 0; padding: 0; height: 1em; background-color: transparent; overflow: hidden; cursor: pointer; box-shadow: 0 0 0 0 transparent; -webkit-appearance: none; appearance: none; }
-input[type='range']::-webkit-slider-thumb { height: .9em; width: .9em; background-color: hsl(180, 54%, 61%); box-shadow: var(--range-shadow); border-radius: var(--radius-sm); }
+input[type='range']::-webkit-slider-thumb { height: .9em; width: .9em; background-color: hsl(180, 54%, 61%); box-shadow: var(--range-shadow); border-radius: var(--radius-xs); }
 input[type='range']::-webkit-slider-runnable-track, input[type='range']::-webkit-slider-thumb { -webkit-appearance: none; }
 input[type='range']::-moz-range-thumb { height: .9em; width: .9em; background-color: hsl(180, 54%, 61%); box-shadow: var(--range-shadow); }
 input[type='range']::-moz-range-track, input[type='range']::-webkit-slider-runnable-track { border: none; background: none; width: 100%; height: 100%; }
diff --git a/modules/paths.py b/modules/paths.py
index 7b43c6868..b1761a811 100644
--- a/modules/paths.py
+++ b/modules/paths.py
@@ -100,6 +100,7 @@ def create_paths(opts):
     create_path(fix_path('ckpt_dir'))
     create_path(fix_path('diffusers_dir'))
     create_path(fix_path('vae_dir'))
+    create_path(fix_path('unet_dir'))
     create_path(fix_path('lora_dir'))
     create_path(fix_path('embeddings_dir'))
     create_path(fix_path('hypernetwork_dir'))
diff --git a/modules/sd_models.py b/modules/sd_models.py
index d72376db7..060fe00ad 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -20,7 +20,7 @@ from omegaconf import OmegaConf
 import tomesd
 from transformers import logging as transformers_logging
 from ldm.util import instantiate_from_config
-from modules import paths, shared, shared_items, shared_state, modelloader, devices, script_callbacks, sd_vae, errors, hashes, sd_models_config, sd_models_compile, sd_hijack_accelerate
+from modules import paths, shared, shared_items, shared_state, modelloader, devices, script_callbacks, sd_vae, sd_unet, errors, hashes, sd_models_config, sd_models_compile, sd_hijack_accelerate
 from modules.timer import Timer
 from modules.memstats import memory_stats
 from modules.modeldata import model_data
@@ -1113,6 +1113,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
         if hasattr(sd_model, "set_progress_bar_config"):
             sd_model.set_progress_bar_config(bar_format='Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining}', ncols=80, colour='#327fba')
 
+        sd_unet.load_unet(sd_model)
         set_diffuser_options(sd_model, vae, op)
 
         if op == 'refiner' and shared.opts.diffusers_move_refiner:
@@ -1134,15 +1135,14 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
         shared.log.error("Failed to load diffusers model")
         errors.display(e, "loading Diffusers model")
 
-    if sd_model is not None:
-        from modules.textual_inversion import textual_inversion
-        sd_model.embedding_db = textual_inversion.EmbeddingDatabase()
-        if op == 'refiner':
-            model_data.sd_refiner = sd_model
-        else:
-            model_data.sd_model = sd_model
-        sd_model.embedding_db.add_embedding_dir(shared.opts.embeddings_dir)
-        sd_model.embedding_db.load_textual_inversion_embeddings(force_reload=True)
+    from modules.textual_inversion import textual_inversion
+    sd_model.embedding_db = textual_inversion.EmbeddingDatabase()
+    if op == 'refiner':
+        model_data.sd_refiner = sd_model
+    else:
+        model_data.sd_model = sd_model
+    sd_model.embedding_db.add_embedding_dir(shared.opts.embeddings_dir)
+    sd_model.embedding_db.load_textual_inversion_embeddings(force_reload=True)
 
     timer.record("load")
     devices.torch_gc(force=True)
diff --git a/modules/sd_unet.py b/modules/sd_unet.py
new file mode 100644
index 000000000..792f80a8d
--- /dev/null
+++ b/modules/sd_unet.py
@@ -0,0 +1,42 @@
+import os
+from modules import shared, devices, files_cache
+
+
+unet_dict = {}
+
+
+def load_unet(model):
+    from diffusers import UNet2DConditionModel
+    from safetensors.torch import load_file
+    if shared.opts.sd_unet == 'None':
+        return
+    if shared.opts.sd_unet not in list(unet_dict):
+        shared.log.error(f'UNet model not found: {shared.opts.sd_unet}')
+        return
+    if not hasattr(model, 'unet') or model.unet is None:
+        shared.log.error('UNet not found in current model')
+        return
+    config_file = os.path.splitext(unet_dict[shared.opts.sd_unet])[0] + '.json'
+    if os.path.exists(config_file):
+        config = shared.readfile(config_file)
+    else:
+        config = None
+        config_file = 'default'
+    try:
+        shared.log.info(f'Loading UNet: name="{shared.opts.sd_unet}" file="{unet_dict[shared.opts.sd_unet]}" config="{config_file}"')
+        unet = UNet2DConditionModel.from_config(model.unet.config if config is None else config).to(devices.device, devices.dtype)
+        state_dict = load_file(unet_dict[shared.opts.sd_unet])
+        unet.load_state_dict(state_dict)
+        model.unet = unet.to(devices.device, devices.dtype_unet)
+    except Exception as e:
+        unet = None
+        shared.log.error(f'Failed to load UNet model: {e}')
+        return
+
+
+def refresh_unet_list():
+    unet_dict.clear()
+    for file in files_cache.list_files(shared.opts.unet_dir, ext_filter=[".safetensors"]):
+        name = os.path.splitext(os.path.basename(file))[0]
+        unet_dict[name] = file
+    shared.log.debug(f'Available UNets: path="{shared.opts.unet_dir}" items={len(unet_dict)}')
diff --git a/modules/shared.py b/modules/shared.py
index e0de4ec77..62dedbfe9 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -386,6 +386,7 @@ options_templates.update(options_section(('sd', "Execution & Models"), {
     "sd_model_checkpoint": OptionInfo(default_checkpoint, "Base model", gr.Dropdown, lambda: {"choices": list_checkpoint_tiles()}, refresh=refresh_checkpoints),
     "sd_model_refiner": OptionInfo('None', "Refiner model", gr.Dropdown, lambda: {"choices": ['None'] + list_checkpoint_tiles()}, refresh=refresh_checkpoints),
     "sd_vae": OptionInfo("Automatic", "VAE model", gr.Dropdown, lambda: {"choices": shared_items.sd_vae_items()}, refresh=shared_items.refresh_vae_list),
+    "sd_unet": OptionInfo("None", "UNET model", gr.Dropdown, lambda: {"choices": shared_items.sd_unet_items()}, refresh=shared_items.refresh_unet_list),
     "sd_checkpoint_autoload": OptionInfo(True, "Model autoload on start"),
     "sd_model_dict": OptionInfo('None', "Use separate base dict", gr.Dropdown, lambda: {"choices": ['None'] + list_checkpoint_tiles()}, refresh=refresh_checkpoints),
     "stream_load": OptionInfo(False, "Load models using stream loading method", gr.Checkbox, {"visible": backend == Backend.ORIGINAL }),
@@ -539,6 +540,7 @@ options_templates.update(options_section(('system-paths', "System Paths"), {
     "diffusers_dir": OptionInfo(os.path.join(paths.models_path, 'Diffusers'), "Folder with Huggingface models", folder=True),
     "hfcache_dir": OptionInfo(os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'hub'), "Folder for Huggingface cache", folder=True),
     "vae_dir": OptionInfo(os.path.join(paths.models_path, 'VAE'), "Folder with VAE files", folder=True),
+    "unet_dir": OptionInfo(os.path.join(paths.models_path, 'UNET'), "Folder with UNET files", folder=True),
     "sd_lora": OptionInfo("", "Add LoRA to prompt", gr.Textbox, {"visible": False}),
     "lora_dir": OptionInfo(os.path.join(paths.models_path, 'Lora'), "Folder with LoRA network(s)", folder=True),
     "lyco_dir": OptionInfo(os.path.join(paths.models_path, 'LyCORIS'), "Folder with LyCORIS network(s)", gr.Text, {"visible": False}),
diff --git a/modules/shared_items.py b/modules/shared_items.py
index 3206a8d1a..a569e4f69 100644
--- a/modules/shared_items.py
+++ b/modules/shared_items.py
@@ -13,6 +13,16 @@ def refresh_vae_list():
     modules.sd_vae.refresh_vae_list()
 
 
+def sd_unet_items():
+    import modules.sd_unet
+    return ["None"] + list(modules.sd_unet.unet_dict)
+
+
+def refresh_unet_list():
+    import modules.sd_unet
+    modules.sd_unet.refresh_unet_list()
+
+
 def list_crossattention(diffusers=False):
     if diffusers:
         return [
diff --git a/webui.py b/webui.py
index cc59f5125..6a722cb2b 100644
--- a/webui.py
+++ b/webui.py
@@ -23,6 +23,7 @@ import modules.lowvram
 import modules.scripts
 import modules.sd_models
 import modules.sd_vae
+import modules.sd_unet
 import modules.progress
 import modules.ui
 import modules.txt2img
@@ -93,6 +94,9 @@ def initialize():
     modules.sd_vae.refresh_vae_list()
     timer.startup.record("vae")
 
+    modules.sd_unet.refresh_unet_list()
+    timer.startup.record("unet")
+
     extensions.list_extensions()
     timer.startup.record("extensions")
 
@@ -117,6 +121,7 @@ def initialize():
     timer.startup.record("upscalers")
 
     shared.opts.onchange("sd_vae", wrap_queued_call(lambda: modules.sd_vae.reload_vae_weights()), call=False)
+    shared.opts.onchange("sd_unet", wrap_queued_call(lambda: modules.sd_unet.load_unet(shared.sd_model)), call=False)
     shared.opts.onchange("temp_dir", gr_tempdir.on_tmpdir_changed)
     timer.startup.record("onchange")