diff --git a/aiserver.py b/aiserver.py
index 0f3a10c5..e61cc3b7 100644
--- a/aiserver.py
+++ b/aiserver.py
@@ -2491,15 +2491,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
                     if(os.path.isdir(vars.custmodpth)):
                         try:
                             tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
-                        except Exception as e:
-                            pass
-                        try:
-                            tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
                         except Exception as e:
                             try:
-                                tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
+                                tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
                             except Exception as e:
-                                tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
+                                try:
+                                    tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
+                                except Exception as e:
+                                    tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
                         try:
                             model     = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", **lowmem)
                         except Exception as e:
@@ -2509,15 +2508,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
                     elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))):
                         try:
                             tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
-                        except Exception as e:
-                            pass
-                        try:
-                            tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
                         except Exception as e:
                             try:
-                                tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
+                                tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
                             except Exception as e:
-                                tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
+                                try:
+                                    tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
+                                except Exception as e:
+                                    tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
                         try:
                             model     = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", **lowmem)
                         except Exception as e:
@@ -2540,15 +2538,14 @@ def load_model(use_gpu=True, gpu_layers=None, disk_layers=None, initial_load=Fal
 
                         try:
                             tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
-                        except Exception as e:
-                            pass
-                        try:
-                            tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
                         except Exception as e:
                             try:
-                                tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
+                                tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
                             except Exception as e:
-                                tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
+                                try:
+                                    tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
+                                except Exception as e:
+                                    tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
                         try:
                             model     = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", **lowmem)
                         except Exception as e:
diff --git a/static/application.js b/static/application.js
index 93ce880c..6cdb531b 100644
--- a/static/application.js
+++ b/static/application.js
@@ -1646,26 +1646,29 @@ function chunkOnBeforeInput(event) {
 	if(buildChunkSetFromNodeArray(getSelectedNodes()).size === 0) {
 		var s = rangy.getSelection();
 		var r = s.getRangeAt(0);
+		var rand = Math.random();
 		if(document.queryCommandSupported && document.execCommand && document.queryCommandSupported('insertHTML')) {
-			document.execCommand('insertHTML', false, '<span id="_EDITOR_SENTINEL_">|</span>');
+			document.execCommand('insertHTML', false, '<span id="_EDITOR_SENTINEL_' + rand + '_">|</span>');
 		} else {
 			var t = document.createTextNode('|');
 			var b = document.createElement('span');
-			b.id = "_EDITOR_SENTINEL_";
+			b.id = "_EDITOR_SENTINEL_" + rand + "_";
 			b.insertNode(t);
 			r.insertNode(b);
 		}
-		var sentinel = document.getElementById("_EDITOR_SENTINEL_");
-		if(sentinel.nextSibling && sentinel.nextSibling.tagName === "CHUNK") {
-			r.selectNodeContents(sentinel.nextSibling);
-			r.collapse(true);
-		} else if(sentinel.previousSibling && sentinel.previousSibling.tagName === "CHUNK") {
-			r.selectNodeContents(sentinel.previousSibling);
-			r.collapse(false);
-		}
-		s.removeAllRanges();
-		s.addRange(r);
-		sentinel.parentNode.removeChild(sentinel);
+		setTimeout(function() {
+			var sentinel = document.getElementById("_EDITOR_SENTINEL_" + rand + "_");
+			if(sentinel.nextSibling && sentinel.nextSibling.tagName === "CHUNK") {
+				r.selectNodeContents(sentinel.nextSibling);
+				r.collapse(true);
+			} else if(sentinel.previousSibling && sentinel.previousSibling.tagName === "CHUNK") {
+				r.selectNodeContents(sentinel.previousSibling);
+				r.collapse(false);
+			}
+			s.removeAllRanges();
+			s.addRange(r);
+			sentinel.parentNode.removeChild(sentinel);
+		}, 1);
 	}
 }
 
diff --git a/templates/index.html b/templates/index.html
index b51fef10..253f6b8a 100644
--- a/templates/index.html
+++ b/templates/index.html
@@ -18,7 +18,7 @@
 	<script src="static/bootstrap.min.js"></script>
 	<script src="static/bootstrap-toggle.min.js"></script>
 	<script src="static/rangy-core.min.js"></script>
-	<script src="static/application.js?ver=1.18.1e"></script>
+	<script src="static/application.js?ver=1.18.1f"></script>
 	<script src="static/favicon.js"></script>
 </head>
 <body>
diff --git a/tpu_mtj_backend.py b/tpu_mtj_backend.py
index 79582867..9c1466f7 100644
--- a/tpu_mtj_backend.py
+++ b/tpu_mtj_backend.py
@@ -1352,15 +1352,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
         if(os.path.isdir(vars.custmodpth)):
             try:
                 tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
-            except Exception as e:
-                pass
-            try:
-                tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
             except Exception as e:
                 try:
-                    tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
+                    tokenizer = AutoTokenizer.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache", use_fast=False)
                 except Exception as e:
-                    tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
+                    try:
+                        tokenizer = GPT2TokenizerFast.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
+                    except Exception as e:
+                        tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
             try:
                 model     = AutoModelForCausalLM.from_pretrained(vars.custmodpth, revision=vars.revision, cache_dir="cache")
             except Exception as e:
@@ -1368,15 +1367,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
         elif(os.path.isdir("models/{}".format(vars.model.replace('/', '_')))):
             try:
                 tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
-            except Exception as e:
-                pass
-            try:
-                tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
             except Exception as e:
                 try:
-                    tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
+                    tokenizer = AutoTokenizer.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache", use_fast=False)
                 except Exception as e:
-                    tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
+                    try:
+                        tokenizer = GPT2TokenizerFast.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
+                    except Exception as e:
+                        tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
             try:
                 model     = AutoModelForCausalLM.from_pretrained("models/{}".format(vars.model.replace('/', '_')), revision=vars.revision, cache_dir="cache")
             except Exception as e:
@@ -1384,15 +1382,14 @@ def load_model(path: str, driver_version="tpu_driver0.1_dev20210607", hf_checkpo
         else:
             try:
                 tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
-            except Exception as e:
-                pass
-            try:
-                tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
             except Exception as e:
                 try:
-                    tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
+                    tokenizer = AutoTokenizer.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache", use_fast=False)
                 except Exception as e:
-                    tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
+                    try:
+                        tokenizer = GPT2TokenizerFast.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
+                    except Exception as e:
+                        tokenizer = GPT2TokenizerFast.from_pretrained("gpt2", revision=vars.revision, cache_dir="cache")
             try:
                 model     = AutoModelForCausalLM.from_pretrained(vars.model, revision=vars.revision, cache_dir="cache")
             except Exception as e: