diff --git a/README.md b/README.md
index 63687dfcd..ee0df19ee 100644
--- a/README.md
+++ b/README.md
@@ -23,12 +23,9 @@ Simplified start script: `automatic.sh`
 
 > ./automatic.sh  
 
-- Start in default mode with optimizations enabled
-
-> ./automatic.sh env  
-
-- Print env info and exit  
-  Example:
+- Start in default mode with optimizations enabled  
+  Additionally print environment info during startup  
+  Example:  
 
       Version: c07487a Tue Jan 24 08:04:31 2023 -0500
       Platform: Ubuntu 22.04.1 LTS 5.15.79.1-microsoft-standard-WSL2 x86_64
@@ -81,10 +78,20 @@ For some Torch optimizations notes, see Wiki
 Fork is compatible with regular **PyTorch 1.13** as well as pre-release of **PyTorch 2.0**  
 See [Wiki](https://github.com/vladmandic/automatic/wiki) for **Torch** optimization notes
 
+<br>
+
+## Scripts
+
+This repository comes with a large collection of scripts that can be used to process inputs, train, generate, and benchmark models  
+
+As well as number of auxiliary scripts that do not rely on **WebUI**, but can be used for end-to-end solutions such as extract frames from videos, etc.  
+
+For full details see [Docs](cli/README.md)
 
 <br>
 
 ## Docs
 
-Everything is in [Wiki](https://github.com/vladmandic/automatic/wiki)  
-Except my current [TODO](TODO.md)  
+- Scripts are in [Scripts](cli/README.md)  
+- Everything else is in [Wiki](https://github.com/vladmandic/automatic/wiki)  
+- Except my current [TODO](TODO.md)  
diff --git a/TODO.md b/TODO.md
index ed7ce678e..df260553f 100644
--- a/TODO.md
+++ b/TODO.md
@@ -72,6 +72,7 @@ Tech that can be integrated as part of the core workflow...
 - [Seed travel](https://github.com/yownas/seed_travel)
 - [Google frame interpolation](https://github.com/google-research/frame-interpolation)
 - [Prompt fusion](https://github.com/ljleb/prompt-fusion-extension)
+- [ControlNet](https://github.com/lllyasviel/ControlNet)
 
 ## Experimental
 
@@ -80,49 +81,4 @@ Cool stuff that is not integrated anywhere...
 - [TensorRT](https://www.photoroom.com/tech/stable-diffusion-25-percent-faster-and-save-seconds/)
 - [GIT](https://huggingface.co/microsoft/git-large-textcaps)
 - Bunch of stuff:<https://pharmapsychotic.com/tools.html>
-- Prevalent colors to interrogate
 - Auto-Sort inputs by face recognition
-
-## Updates
-
-- core library updates:
-  - must run `./automatic.sh install`
-  - note: this is quite a big one so some testing is reccomended after upgrade
-- non-trivial ui updates
-- renamed scripts in `cli/modules` to be more descriptive  
-  if you're using old script names, update them  
-  for example, `ffmpeg.py` is now `video-extract.py`  
-  also possible that there are some bugs due to broken import paths, so testing is welcome  
-- updated script `process.py`
-  - new **brightness dynamic range** check  
-  - new **preview** mode to run all checks but without saving images plus print a summary at the end
-- updated scripts `models-preview.py`  
-  - can generate **lora** previews, note that trigger keywords are inferred from model name so name models carefully  
-  - can generate **hypernetwork** previews  
-- new script: `image-watermark.py`  
-  - optionally strip exif from images
-  - add invisible watermark to images which persists even if user modifies image so we can always track it
-- new script: `palette-extract.py`
-  - creates color palette wheel from image(s)
-- new script: `extract-lora.py`
-  - extract lora from fine-tuned model
-- updated `embedding-preview.py`  
-  - skip existing previews or overwrite them  
-- expose **variation seed** in main ui  
-- integrated **seed travel** functionality into core  
-- integrated `pix2pix` functionality to standard `img2img` workflow  
-  - note: requires **pix2pix** model to be loaded  
-- integrated large `cfg scale` values fix  
-- integrated **model converter**  
-- tested `aesthetic gradients` training, not worth it  
-- updated `image browser`  
-  was broken for a while and maintainer is gone  
-- initial work on **queue management** allowing to submit multiple requests to server  
-- initial work on `lora` integration  
-  can render loras without extensions  
-  can extract lora from fine-tuned model  
-  training prototype in place in `train-lora.py`, not optimized or integrated  
-- initial work on `custom diffusion` integration  
-  no testing so far  
-- spent quite some time making stable-diffusion compatible with upcomming `pytorch` 2.0 release  
-  and testing `dynamo` torch dynamic optimizer and `triton` script compiler  
diff --git a/automatic.sh b/automatic.sh
index 151fc235a..48a05dea8 100755
--- a/automatic.sh
+++ b/automatic.sh
@@ -1,4 +1,4 @@
-#/bin/env bash
+#!/bin/env bash
 
 TF_CPP_MIN_LOG_LEVEL=2
 FORCE_CUDA="1"
@@ -11,7 +11,7 @@ CUDA_AUTO_BOOST=1
 CUDA_DEVICE_DEFAULT_PERSISTING_L2_CACHE_PERCENTAGE_LIMIT=0
 
 if [ "$PYTHON" == "" ]; then
-  PYTHON=`which python`
+  PYTHON=$(which python)
 fi
 
 CMD="launch.py --api --xformers --disable-console-progressbars --gradio-queue --skip-version-check --cors-allow-origins=http://127.0.0.1:7860"
@@ -43,27 +43,27 @@ done
 
 echo "SD server: $MODE"
 
-VER=`git log -1 --pretty=format:"%h %ad"`
-LSB=`lsb_release -ds 2>/dev/null`
-UN=`uname -rm 2>/dev/null`
+VER=$(git log -1 --pretty=format:"%h %ad")
+LSB=$(lsb_release -ds 2>/dev/null)
+UNAME=$(uname -rm 2>/dev/null)
 echo "Version: $VER"
-echo "Platform: $LSB $UN"
-$PYTHON -c 'import torch; import platform; print("Python:", platform.python_version(), "Torch:", torch.__version__, "CUDA:", torch.version.cuda, "cuDNN:", torch.backends.cudnn.version(), "GPU:", torch.cuda.get_device_name(torch.cuda.current_device()), "Arch:", torch.cuda.get_device_capability());'
+echo "Platform: $LSB $UNAME"
+"$PYTHON" -c 'import torch; import platform; print("Python:", platform.python_version(), "Torch:", torch.__version__, "CUDA:", torch.version.cuda, "cuDNN:", torch.backends.cudnn.version(), "GPU:", torch.cuda.get_device_name(torch.cuda.current_device()), "Arch:", torch.cuda.get_device_capability());'
 
-if [ $MODE == install ]; then
-  $PYTHON -m pip --version
+if [ "$MODE" == install ]; then
+  "$PYTHON" -m pip --version
   echo "Installing general requirements"
-  $PYTHON -m pip install --disable-pip-version-check --quiet --no-warn-conflicts --requirement requirements.txt
+  "$PYTHON" -m pip install --disable-pip-version-check --quiet --no-warn-conflicts --requirement requirements.txt
   echo "Installing versioned requirements"
-  $PYTHON -m pip install --disable-pip-version-check --quiet --no-warn-conflicts --requirement requirements_versions.txt
+  "$PYTHON" -m pip install --disable-pip-version-check --quiet --no-warn-conflicts --requirement requirements_versions.txt
   echo "Updating submodules"
   git submodule update --rebase --remote
   exit 0
 fi
 
-if [ $MODE == clean ]; then
+if [ "$MODE" == clean ]; then
   CMD="--disable-opt-split-attention --disable-console-progressbars --api"
-  $PYTHON launch.py $CMD
+  "$PYTHON" launch.py $CMD
   exit 0
 fi
 
@@ -75,4 +75,4 @@ if [ $MODE == optimized ]; then
   CMD="$CMD"
 fi
 
-exec accelerate launch --no_python --quiet --num_cpu_threads_per_process=6 $PYTHON $CMD
+exec accelerate launch --no_python --quiet --num_cpu_threads_per_process=6 "$PYTHON" $CMD
diff --git a/cli/modules/preview-models.py b/cli/modules/preview-models.py
index 7be4fd6f8..7815097bc 100755
--- a/cli/modules/preview-models.py
+++ b/cli/modules/preview-models.py
@@ -15,7 +15,7 @@ from generate import sd, generate
 
 
 default = 'sd-v15-runwayml.ckpt [cc6cb27103]'
-embeddings = ['blonde', 'bruntette', 'sexy', 'naked', 'mia', 'lin', 'kelly', 'hanna', 'rreid-random-v0']
+embeddings = ['blonde', 'bruntette', 'sexy', 'naked', 'ti-mia', 'ti-lin', 'ti-kelly', 'ti-hanna', 'ti-rreid-random']
 exclude = ['sd-v20', 'sd-v21', 'inpainting', 'pix2pix']
 prompt = "photo of <keyword> <embedding>, photograph, posing, pose, high detailed, intricate, elegant, sharp focus, skin texture, looking forward, facing camera, 135mm, shot on dslr, canon 5d, 4k, modelshoot style, cinematic lighting"
 options = Map({
@@ -32,6 +32,7 @@ options = Map({
         'width': 512,
         'height': 512,
     },
+    'format': '.jpg',
     'paths': {
         "root": "/mnt/c/Users/mandi/OneDrive/Generative/Generate",
         "generate": "image",
@@ -43,11 +44,11 @@ options = Map({
         "sd_vae": "vae-ft-mse-840000-ema-pruned.ckpt",
     },
     'lora': {
-        'strength': 0.8,
+        'strength': 0.9,
     },
     'hypernetwork': {
         'keyword': 'beautiful sexy woman',
-        'strength': 1.0,
+        'strength': 0.9,
     },
 })
 
@@ -91,7 +92,7 @@ async def models(params):
     log.info({ 'total jobs': len(models) * len(embeddings) * options.generate.batch_size, 'per-model': len(embeddings) * options.generate.batch_size })
     log.info(json.dumps(options, indent=2))
     for model in models:
-        fn = os.path.join(dir, model + '.png')
+        fn = os.path.join(dir, model + options.format)
         if os.path.exists(fn) and len(params.input) == 0: # if model preview exists and not manually included
             log.info({ 'model preview exists': model })
             continue
@@ -139,15 +140,18 @@ async def lora(params):
     models = [f.stem for f in models1 + models2]
     log.info({ 'loras': len(models) })
     for model in models:
-        fn = os.path.join(dir, model + '.png')
+        fn = os.path.join(dir, model + options.format)
         if os.path.exists(fn) and len(params.input) == 0: # if model preview exists and not manually included
             log.info({ 'lora preview exists': model })
             continue
         images = []
         labels = []
         t0 = time.time()
-        keyword = model.replace('-', ' ')
-        options.generate.prompt = prompt.replace('<keyword>', f'\"{keyword}\"')
+        import re
+        keywords = re.sub('\d', '', model)
+        keywords = keywords.replace('-v', ' ').replace('-', ' ').strip().split(' ')
+        keyword = '\"' + '\" \"'.join(keywords) + '\"'
+        options.generate.prompt = prompt.replace('<keyword>', keyword)
         options.generate.prompt = options.generate.prompt.replace('<embedding>', '')
         options.generate.prompt += f' <lora:{model}:{options.lora.strength}>'
         log.info({ 'lora generating': model, 'keyword': keyword, 'prompt': options.generate.prompt })
@@ -175,7 +179,7 @@ async def hypernetwork(params):
     models = [f.stem for f in Path(dir).glob('*.pt')]
     log.info({ 'loras': len(models) })
     for model in models:
-        fn = os.path.join(dir, model + '.png')
+        fn = os.path.join(dir, model + options.format)
         if os.path.exists(fn) and len(params.input) == 0: # if model preview exists and not manually included
             log.info({ 'hypernetwork preview exists': model })
             continue
@@ -186,7 +190,7 @@ async def hypernetwork(params):
         options.generate.prompt = prompt.replace('<keyword>', options.hypernetwork.keyword)
         options.generate.prompt = options.generate.prompt.replace('<embedding>', '')
         options.generate.prompt = f' <hypernet:{model}:{options.hypernetwork.strength}> ' + options.generate.prompt
-        log.info({ 'lora generating': model, 'keyword': keyword, 'prompt': options.generate.prompt })
+        log.info({ 'hypernetwork generating': model, 'keyword': keyword, 'prompt': options.generate.prompt })
         data = await generate(options = options, quiet=True)
         if 'image' in data:
             for img in data['image']:
diff --git a/cli/modules/process.py b/cli/modules/process.py
index 7ea370628..817f97a98 100755
--- a/cli/modules/process.py
+++ b/cli/modules/process.py
@@ -7,6 +7,7 @@ process people images
     - visible: is face or body detected
     - in frame: for face based on box, for body based on number of visible keypoints
     - resolution: is cropped image still of sufficient resolution
+    - optionaly upsample and restore face quality
     - blur: is image sharp enough
     - dynamic range: is image bright enough
     - similarity: compares image to all previously processed images to see if its unique enough
@@ -40,20 +41,29 @@ from sdapi import postsync
 
 
 params = Map({
+    # general settings, do not modify
     'src': '', # source folder
     'dst': '', # destination folder
-    'format': '.jpg', # image format
-    'extract_face': True, # extract face from image
-    'extract_body': True, # extract face from image
     'clear_dst': True, # remove all files from destination at the start
+    'format': '.jpg', # image format
     'target_size': 512, # target resolution
     'square_images': True, # should output images be squared
+    'segmentation_model': 0, # segmentation model 0/general 1/landscape
+    'segmentation_background': (192, 192, 192), # segmentation background color
     'blur_samplesize': 60, # sample size to use for blur detection
+    'similarity_size': 64, # base similarity detection on reduced images
+    # face processing settings
+    'extract_face': True, # extract face from image
     'face_score': 0.7, # min face detection score
     'face_pad': 0.2, # pad face image percentage
     'face_model': 1, # which face model to use 0/close-up 1/standard
     'face_blur_score': 1.5, # max score for face blur detection
     'face_range_score': 0.15, # min score for face dynamic range detection
+    'face_restore': True, # attempt to restore face quality
+    'face_upscale': True, # attempt to scale small faces
+    'face_segmentation': False, # segmentation enabled
+    # body processing settings
+    'extract_body': True, # extract face from image
     'body_score': 0.9, # min body detection score
     'body_visibility': 0.5, # min visibility score for each detected body part
     'body_parts': 15, # min number of detected body parts with sufficient visibility
@@ -61,16 +71,13 @@ params = Map({
     'body_model': 2, # body model to use 0/low 1/medium 2/high
     'body_blur_score': 1.8, # max score for body blur detection
     'body_range_score': 0.15, # min score for body dynamic range detection
-    'segmentation_face': False, # segmentation enabled
-    'segmentation_body': False, # segmentation enabled
-    'segmentation_model': 0, # segmentation model 0/general 1/landscape
-    'segmentation_background': (192, 192, 192), # segmentation background color
+    'body_segmentation': False, # segmentation enabled
+    # similarity detection settings
     'similarity_score': 0.8, # maximum similarity score before image is discarded
-    'similarity_size': 64, # base similarity detection on reduced images
-    'interrogate_model': ['clip', 'deepdanbooru'], # interrogate model
+    # interrogate settings
+    'interrogate_model': ['clip', 'deepdanbooru'], # interrogate models
+    'interrogate_captions': True, # write captions to file
     'tag_limit': 5, # number of tags to extract
-    'face_restore': True, # attempt to restore face quality
-    'face_upscale': True, # attempt to scale small faces
 })
 face_model = None
 body_model = None
@@ -181,6 +188,9 @@ def extract_face(img):
         })
         original = [cropped.size[0], cropped.size[1]]
         res = postsync('/sdapi/v1/extra-single-image', kwargs)
+        if 'image' not in res:
+            log.error({ 'process face': 'upscale failed' })
+            raise ValueError('upscale failed')
         cropped = Image.open(io.BytesIO(base64.b64decode(res['image'])))
         kwargs.image = [cropped.size[0], cropped.size[1]]
         upscaled = [cropped.size[0], cropped.size[1]]
@@ -195,7 +205,7 @@ def extract_face(img):
     if params.square_images:
         squared = Image.new('RGB', (params.target_size, params.target_size))
         squared.paste(cropped, (0, 0))
-        if params.segmentation_face:
+        if params.face_segmentation:
            squared = segmentation(squared)
     else:
         squared = cropped
@@ -258,7 +268,7 @@ def extract_body(img):
     if params.square_images:
         squared = Image.new('RGB', (params.target_size, params.target_size))
         squared.paste(cropped, (0, 0))
-        if params.segmentation_body:
+        if params.body_segmentation:
            squared = segmentation(squared)
     else:
         squared = cropped
@@ -293,7 +303,7 @@ def encode(img):
         return encoded
 
 
-def interrogate(img, fn, txt):
+def interrogate(img, fn):
     if len(params.interrogate_model) == 0:
         return
     caption = ''
@@ -308,7 +318,7 @@ def interrogate(img, fn, txt):
             tag = res.caption if 'caption' in res else ''
             tags = tag.split(',')
             tags = [t.replace('(', '').replace(')', '').split(':')[0].strip() for t in tags]
-        if txt:
+        if params.interrogate_captions:
             file = fn.replace(params.format, '.txt')
             f = open(file, 'w')
             f.write(caption)
@@ -323,7 +333,7 @@ def interrogate(img, fn, txt):
 i = {}
 metadata = Map({})
 
-def process_file(f: str, dst: str = None, preview: bool = False, offline: bool = False, txt: bool = True):
+def process_file(f: str, dst: str = None, preview: bool = False, offline: bool = False, txt = None):
 
     def save(img, f, what):
         i[what] = i.get(what, 0) + 1
@@ -338,7 +348,7 @@ def process_file(f: str, dst: str = None, preview: bool = False, offline: bool =
         if not preview:
             img.save(fn)
             if not offline:
-                caption, tags = interrogate(img, fn, txt)
+                caption, tags = interrogate(img, fn)
         metadata[fn] = { 'caption': caption, 'tags': tags }
         return fn
 
@@ -350,6 +360,8 @@ def process_file(f: str, dst: str = None, preview: bool = False, offline: bool =
         return 0, {}
 
     image = ImageOps.exif_transpose(image) # rotate image according to EXIF orientation
+    if txt is not None:
+        params.interrogate_captions = txt
 
     if image.width < 512 or image.height < 512:
         log.info({ 'process skip': 'low resolution', 'resolution': [image.width, image.height] })
diff --git a/cli/train-lora.py b/cli/train-lora.py
index 2e8049e8e..7246a988a 100755
--- a/cli/train-lora.py
+++ b/cli/train-lora.py
@@ -182,12 +182,16 @@ if __name__ == '__main__':
     if not args.noprocess:
         # preprocess
         for f in files:
-            res, metadata = modules.process.process_file(f = f, dst = dir, preview = False, offline = args.offline, txt = False)
+            try:
+                res, metadata = modules.process.process_file(f = f, dst = dir, preview = False, offline = args.offline, txt = False)
+            except ValueError as e:
+                exit(1)                
         modules.process.unload_models()
         mem_stats()
         if args.tag is not None:
             for name, item in metadata.items():
                 item['tags'].insert(0, args.tag)
+                item['tags'] = ', '.join(item['tags'])
         with open(json_file, "w") as outfile:
             outfile.write(json.dumps(metadata, indent=2))
         log.info({ 'processed': res, 'inputs': len(files), 'metadata': json_file, 'path': dir })
diff --git a/config.json b/config.json
index e444c4f4d..3acf810ab 100644
--- a/config.json
+++ b/config.json
@@ -34,7 +34,7 @@
     "eta_ddim": 0.0,
     "eta_noise_seed_delta": 0,
     "export_for_4chan": false,
-    "extra_networks_default_multiplier": 1,
+    "extra_networks_default_multiplier": 0.9,
     "extra_networks_default_view": "cards",
     "face_restoration_model": "CodeFormer",
     "face_restoration_unload": false,
diff --git a/extensions-builtin/Lora/ui_extra_networks_lora.py b/extensions-builtin/Lora/ui_extra_networks_lora.py
index 22cabcb0f..3f7c597b9 100644
--- a/extensions-builtin/Lora/ui_extra_networks_lora.py
+++ b/extensions-builtin/Lora/ui_extra_networks_lora.py
@@ -15,7 +15,7 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage):
     def list_items(self):
         for name, lora_on_disk in lora.available_loras.items():
             path, ext = os.path.splitext(lora_on_disk.filename)
-            previews = [path + ".png", path + ".preview.png"]
+            previews = [path + ".png", path + ".preview.png", path + ".jpg", path + ".preview.jpg", path + ".jpeg", path + ".preview.jpeg", path + ".webp", path + ".preview.webp"]
 
             preview = None
             for file in previews:
@@ -28,10 +28,9 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage):
                 "filename": path,
                 "preview": preview,
                 "search_term": self.search_terms_from_path(lora_on_disk.filename),
-                "prompt": json.dumps(f"<lora:{name}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"),
-                "local_preview": path + ".png",
+                "prompt": json.dumps(f"<lora:{name}:{str(shared.opts.extra_networks_default_multiplier)}>"),
+                "local_preview": f"{path}.{shared.opts.samples_format}",
             }
 
     def allowed_directories_for_previews(self):
         return [shared.cmd_opts.lora_dir]
-
diff --git a/extensions-builtin/sd-dynamic-thresholding b/extensions-builtin/sd-dynamic-thresholding
index 681a5ffe7..6c76a48a1 160000
--- a/extensions-builtin/sd-dynamic-thresholding
+++ b/extensions-builtin/sd-dynamic-thresholding
@@ -1 +1 @@
-Subproject commit 681a5ffe7bcc4cd00890339a32a7e903f9cf6e7c
+Subproject commit 6c76a48a1f802287cfceacd912149c5141b22031
diff --git a/extensions-builtin/seed_travel b/extensions-builtin/seed_travel
index 8f818f18f..185ae54e9 160000
--- a/extensions-builtin/seed_travel
+++ b/extensions-builtin/seed_travel
@@ -1 +1 @@
-Subproject commit 8f818f18f258ac4e53a34c1219819da497e97be1
+Subproject commit 185ae54e93c560111a7053bfd31be187b9ed1246
diff --git a/extensions-builtin/stable-diffusion-webui-images-browser b/extensions-builtin/stable-diffusion-webui-images-browser
index 0416810ad..c25e8a73f 160000
--- a/extensions-builtin/stable-diffusion-webui-images-browser
+++ b/extensions-builtin/stable-diffusion-webui-images-browser
@@ -1 +1 @@
-Subproject commit 0416810adf4827aa36a032dc7beed94ba6dcb954
+Subproject commit c25e8a73f3676b197c2c0bd37f7d493d108e521d
diff --git a/modules/extensions.py b/modules/extensions.py
index 5e12b1aaa..1975fca1c 100644
--- a/modules/extensions.py
+++ b/modules/extensions.py
@@ -2,6 +2,7 @@ import os
 import sys
 import traceback
 
+import time
 import git
 
 from modules import paths, shared
@@ -25,6 +26,7 @@ class Extension:
         self.status = ''
         self.can_update = False
         self.is_builtin = is_builtin
+        self.version = ''
 
         repo = None
         try:
@@ -40,6 +42,10 @@ class Extension:
             try:
                 self.remote = next(repo.remote().urls, None)
                 self.status = 'unknown'
+                head = repo.head.commit
+                ts = time.asctime(time.gmtime(repo.head.commit.committed_date))
+                self.version = f'{head.hexsha[:7]} ({ts})'
+
             except Exception:
                 self.remote = None
 
diff --git a/modules/ui.py b/modules/ui.py
index cbe6b9310..32d49e10d 100644
--- a/modules/ui.py
+++ b/modules/ui.py
@@ -1012,48 +1012,6 @@ def create_ui():
         }
         return interp_descriptions[value]
 
-    with gr.Blocks(analytics_enabled=False) as modelmerger_interface:
-        with gr.Row().style(equal_height=False):
-            with gr.Column(variant='compact'):
-                interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description")
-
-                with FormRow(elem_id="modelmerger_models"):
-                    primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
-                    create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
-
-                    secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
-                    create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
-
-                    tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
-                    create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
-
-                custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
-                interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
-                interp_method = gr.Radio(choices=["No interpolation", "Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
-                interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
-
-                with FormRow():
-                    checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
-                    save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
-
-                with FormRow():
-                    with gr.Column():
-                        config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
-
-                    with gr.Column():
-                        with FormRow():
-                            bake_in_vae = gr.Dropdown(choices=["None"] + list(sd_vae.vae_dict), value="None", label="Bake in VAE", elem_id="modelmerger_bake_in_vae")
-                            create_refresh_button(bake_in_vae, sd_vae.refresh_vae_list, lambda: {"choices": ["None"] + list(sd_vae.vae_dict)}, "modelmerger_refresh_bake_in_vae")
-
-                with FormRow():
-                    discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights")
-
-                with gr.Row():
-                    modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
-
-            with gr.Column(variant='compact', elem_id="modelmerger_results_container"):
-                with gr.Group(elem_id="modelmerger_results_panel"):
-                    modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False)
 
     with gr.Blocks(analytics_enabled=False) as train_interface:
         with gr.Row().style(equal_height=False):
@@ -1062,6 +1020,49 @@ def create_ui():
         with gr.Row(variant="compact").style(equal_height=False):
             with gr.Tabs(elem_id="train_tabs"):
 
+                with gr.Tab(label="Merge models") as modelmerger_interface:
+                    with gr.Row().style(equal_height=False):
+                        with gr.Column(variant='compact'):
+                            interp_description = gr.HTML(value=update_interp_description("Weighted sum"), elem_id="modelmerger_interp_description")
+
+                            with FormRow(elem_id="modelmerger_models"):
+                                primary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_primary_model_name", label="Primary model (A)")
+                                create_refresh_button(primary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_A")
+
+                                secondary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_secondary_model_name", label="Secondary model (B)")
+                                create_refresh_button(secondary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_B")
+
+                                tertiary_model_name = gr.Dropdown(modules.sd_models.checkpoint_tiles(), elem_id="modelmerger_tertiary_model_name", label="Tertiary model (C)")
+                                create_refresh_button(tertiary_model_name, modules.sd_models.list_models, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, "refresh_checkpoint_C")
+
+                            custom_name = gr.Textbox(label="Custom Name (Optional)", elem_id="modelmerger_custom_name")
+                            interp_amount = gr.Slider(minimum=0.0, maximum=1.0, step=0.05, label='Multiplier (M) - set to 0 to get model A', value=0.3, elem_id="modelmerger_interp_amount")
+                            interp_method = gr.Radio(choices=["No interpolation", "Weighted sum", "Add difference"], value="Weighted sum", label="Interpolation Method", elem_id="modelmerger_interp_method")
+                            interp_method.change(fn=update_interp_description, inputs=[interp_method], outputs=[interp_description])
+
+                            with FormRow():
+                                checkpoint_format = gr.Radio(choices=["ckpt", "safetensors"], value="ckpt", label="Checkpoint format", elem_id="modelmerger_checkpoint_format")
+                                save_as_half = gr.Checkbox(value=False, label="Save as float16", elem_id="modelmerger_save_as_half")
+
+                            with FormRow():
+                                with gr.Column():
+                                    config_source = gr.Radio(choices=["A, B or C", "B", "C", "Don't"], value="A, B or C", label="Copy config from", type="index", elem_id="modelmerger_config_method")
+
+                                with gr.Column():
+                                    with FormRow():
+                                        bake_in_vae = gr.Dropdown(choices=["None"] + list(sd_vae.vae_dict), value="None", label="Bake in VAE", elem_id="modelmerger_bake_in_vae")
+                                        create_refresh_button(bake_in_vae, sd_vae.refresh_vae_list, lambda: {"choices": ["None"] + list(sd_vae.vae_dict)}, "modelmerger_refresh_bake_in_vae")
+
+                            with FormRow():
+                                discard_weights = gr.Textbox(value="", label="Discard weights with matching name", elem_id="modelmerger_discard_weights")
+
+                            with gr.Row():
+                                modelmerger_merge = gr.Button(elem_id="modelmerger_merge", value="Merge", variant='primary')
+
+                        with gr.Column(variant='compact', elem_id="modelmerger_results_container"):
+                            with gr.Group(elem_id="modelmerger_results_panel"):
+                                modelmerger_result = gr.HTML(elem_id="modelmerger_result", show_label=False)
+
                 with gr.Tab(label="Create embedding"):
                     new_embedding_name = gr.Textbox(label="Name", elem_id="train_new_embedding_name")
                     initialization_text = gr.Textbox(label="Initialization text", value="*", elem_id="train_initialization_text")
@@ -1539,7 +1540,7 @@ def create_ui():
         (img2img_interface, "From Image", "img2img"),
         (extras_interface, "Process", "extras"),
         (pnginfo_interface, "Image Info", "pnginfo"),
-        (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
+        # (modelmerger_interface, "Checkpoint Merger", "modelmerger"),
         (train_interface, "Train", "ti"),
     ]
 
diff --git a/modules/ui_extensions.py b/modules/ui_extensions.py
index 37d30e1f2..bd4308ef0 100644
--- a/modules/ui_extensions.py
+++ b/modules/ui_extensions.py
@@ -80,6 +80,7 @@ def extension_table():
             <tr>
                 <th><abbr title="Use checkbox to enable the extension; it will be enabled or disabled when you click apply button">Extension</abbr></th>
                 <th>URL</th>
+                <th><abbr title="Extension version">Version</abbr></th>
                 <th><abbr title="Use checkbox to mark the extension for update; it will be updated when you click apply button">Update</abbr></th>
             </tr>
         </thead>
@@ -87,11 +88,7 @@ def extension_table():
     """
 
     for ext in extensions.extensions:
-        remote = ""
-        if ext.is_builtin:
-            remote = "built-in"
-        elif ext.remote:
-            remote = f"""<a href="{html.escape(ext.remote or '')}" target="_blank">{html.escape("built-in" if ext.is_builtin else ext.remote or '')}</a>"""
+        remote = f"""<a href="{html.escape(ext.remote or '')}" target="_blank">{html.escape("built-in" if ext.is_builtin else ext.remote or '')}</a>"""
 
         if ext.can_update:
             ext_status = f"""<label><input class="gr-check-radio gr-checkbox" name="update_{html.escape(ext.name)}" checked="checked" type="checkbox">{html.escape(ext.status)}</label>"""
@@ -102,6 +99,7 @@ def extension_table():
             <tr>
                 <td><label><input class="gr-check-radio gr-checkbox" name="enable_{html.escape(ext.name)}" type="checkbox" {'checked="checked"' if ext.enabled else ''}>{html.escape(ext.name)}</label></td>
                 <td>{remote}</td>
+                <td>{ext.version}</td>
                 <td{' class="extension_status"' if ext.remote is not None else ''}>{ext_status}</td>
             </tr>
     """
diff --git a/modules/ui_extra_networks_checkpoints.py b/modules/ui_extra_networks_checkpoints.py
index 04097a794..d80950c72 100644
--- a/modules/ui_extra_networks_checkpoints.py
+++ b/modules/ui_extra_networks_checkpoints.py
@@ -17,7 +17,7 @@ class ExtraNetworksPageCheckpoints(ui_extra_networks.ExtraNetworksPage):
         checkpoint: sd_models.CheckpointInfo
         for name, checkpoint in sd_models.checkpoints_list.items():
             path, ext = os.path.splitext(checkpoint.filename)
-            previews = [path + ".png", path + ".preview.png"]
+            previews = [path + ".png", path + ".preview.png", path + ".jpg", path + ".preview.jpg", path + ".jpeg", path + ".preview.jpeg", path + ".webp", path + ".preview.webp"]
 
             preview = None
             for file in previews:
@@ -31,7 +31,8 @@ class ExtraNetworksPageCheckpoints(ui_extra_networks.ExtraNetworksPage):
                 "preview": preview,
                 "search_term": self.search_terms_from_path(checkpoint.filename) + " " + (checkpoint.sha256 or ""),
                 "onclick": '"' + html.escape(f"""return selectCheckpoint({json.dumps(name)})""") + '"',
-                "local_preview": path + ".png",
+                "local_preview": f"{path}.{shared.opts.samples_format}",
+
             }
 
     def allowed_directories_for_previews(self):
diff --git a/modules/ui_extra_networks_hypernets.py b/modules/ui_extra_networks_hypernets.py
index 578510887..f5541d13d 100644
--- a/modules/ui_extra_networks_hypernets.py
+++ b/modules/ui_extra_networks_hypernets.py
@@ -14,7 +14,7 @@ class ExtraNetworksPageHypernetworks(ui_extra_networks.ExtraNetworksPage):
     def list_items(self):
         for name, path in shared.hypernetworks.items():
             path, ext = os.path.splitext(path)
-            previews = [path + ".png", path + ".preview.png"]
+            previews = [path + ".png", path + ".preview.png", path + ".jpg", path + ".preview.jpg", path + ".jpeg", path + ".preview.jpeg", path + ".webp", path + ".preview.webp"]
 
             preview = None
             for file in previews:
@@ -27,8 +27,8 @@ class ExtraNetworksPageHypernetworks(ui_extra_networks.ExtraNetworksPage):
                 "filename": path,
                 "preview": preview,
                 "search_term": self.search_terms_from_path(path),
-                "prompt": json.dumps(f"<hypernet:{name}:") + " + opts.extra_networks_default_multiplier + " + json.dumps(">"),
-                "local_preview": path + ".png",
+                "prompt": json.dumps(f"<hypernet:{name}:{str(shared.opts.extra_networks_default_multiplier)}>"),
+                "local_preview": f"{path}.{shared.opts.samples_format}",
             }
 
     def allowed_directories_for_previews(self):
diff --git a/modules/ui_extra_networks_textual_inversion.py b/modules/ui_extra_networks_textual_inversion.py
index bb64eb81e..2b5fef55f 100644
--- a/modules/ui_extra_networks_textual_inversion.py
+++ b/modules/ui_extra_networks_textual_inversion.py
@@ -1,7 +1,7 @@
 import json
 import os
 
-from modules import ui_extra_networks, sd_hijack
+from modules import ui_extra_networks, sd_hijack, shared
 
 
 class ExtraNetworksPageTextualInversion(ui_extra_networks.ExtraNetworksPage):
@@ -16,10 +16,13 @@ class ExtraNetworksPageTextualInversion(ui_extra_networks.ExtraNetworksPage):
         for embedding in sd_hijack.model_hijack.embedding_db.word_embeddings.values():
             path, ext = os.path.splitext(embedding.filename)
             preview_file = path + ".preview.png"
+            previews = [path + ".preview.png", path + ".preview.jpg", path + ".preview.jpeg", path + ".preview.webp"]
 
             preview = None
-            if os.path.isfile(preview_file):
-                preview = self.link_preview(preview_file)
+            for file in previews:
+                if os.path.isfile(file):
+                    preview = self.link_preview(file)
+                    break
 
             yield {
                 "name": embedding.name,
@@ -27,7 +30,7 @@ class ExtraNetworksPageTextualInversion(ui_extra_networks.ExtraNetworksPage):
                 "preview": preview,
                 "search_term": self.search_terms_from_path(embedding.filename),
                 "prompt": json.dumps(embedding.name),
-                "local_preview": path + ".preview.png",
+                "local_preview": f"{path}.preview.{shared.opts.samples_format}",
             }
 
     def allowed_directories_for_previews(self):
diff --git a/ui-config.json b/ui-config.json
index fd75e30ce..ddcdc0915 100644
--- a/ui-config.json
+++ b/ui-config.json
@@ -1130,5 +1130,44 @@
     "customscript/dynamic_thresholding.py/img2img/Power Scheduler Value/value": 4.0,
     "customscript/dynamic_thresholding.py/img2img/Power Scheduler Value/minimum": 0.0,
     "customscript/dynamic_thresholding.py/img2img/Power Scheduler Value/maximum": 15.0,
-    "customscript/dynamic_thresholding.py/img2img/Power Scheduler Value/step": 0.5
+    "customscript/dynamic_thresholding.py/img2img/Power Scheduler Value/step": 0.5,
+    "customscript/seed_travel.py/txt2img/Interpolation rate/visible": true,
+    "customscript/seed_travel.py/txt2img/Interpolation rate/value": "Linear",
+    "customscript/seed_travel.py/txt2img/Rate strength/visible": true,
+    "customscript/seed_travel.py/txt2img/Rate strength/value": 3,
+    "customscript/seed_travel.py/txt2img/Rate strength/minimum": 0.0,
+    "customscript/seed_travel.py/txt2img/Rate strength/maximum": 10.0,
+    "customscript/seed_travel.py/txt2img/Rate strength/step": 0.1,
+    "customscript/seed_travel.py/img2img/Interpolation rate/visible": true,
+    "customscript/seed_travel.py/img2img/Interpolation rate/value": "Linear",
+    "customscript/seed_travel.py/img2img/Rate strength/visible": true,
+    "customscript/seed_travel.py/img2img/Rate strength/value": 3,
+    "customscript/seed_travel.py/img2img/Rate strength/minimum": 0.0,
+    "customscript/seed_travel.py/img2img/Rate strength/maximum": 10.0,
+    "customscript/seed_travel.py/img2img/Rate strength/step": 0.1,
+    "train/Primary model (A)/visible": true,
+    "train/Primary model (A)/value": null,
+    "train/Secondary model (B)/visible": true,
+    "train/Secondary model (B)/value": null,
+    "train/Tertiary model (C)/visible": true,
+    "train/Tertiary model (C)/value": null,
+    "train/Custom Name (Optional)/visible": true,
+    "train/Custom Name (Optional)/value": "",
+    "train/Multiplier (M) - set to 0 to get model A/visible": true,
+    "train/Multiplier (M) - set to 0 to get model A/value": 0.3,
+    "train/Multiplier (M) - set to 0 to get model A/minimum": 0.0,
+    "train/Multiplier (M) - set to 0 to get model A/maximum": 1.0,
+    "train/Multiplier (M) - set to 0 to get model A/step": 0.05,
+    "train/Interpolation Method/visible": true,
+    "train/Interpolation Method/value": "Weighted sum",
+    "train/Checkpoint format/visible": true,
+    "train/Checkpoint format/value": "ckpt",
+    "train/Save as float16/visible": true,
+    "train/Save as float16/value": true,
+    "train/Copy config from/visible": true,
+    "train/Copy config from/value": "A, B or C",
+    "train/Bake in VAE/visible": true,
+    "train/Bake in VAE/value": "None",
+    "train/Discard weights with matching name/visible": true,
+    "train/Discard weights with matching name/value": ""
 }
\ No newline at end of file