diff --git a/aiserver.py b/aiserver.py
index e6e5c80b..e4280aec 100644
--- a/aiserver.py
+++ b/aiserver.py
@@ -82,6 +82,7 @@ class vars:
     submission  = ""     # Same as above, but after applying input formatting
     lastctx     = ""     # The last context submitted to the generator
     model       = ""     # Model ID string chosen at startup
+    model_orig  = ""     # Original model string before being changed by auto model type detection
     model_type  = ""     # Model Type (Automatically taken from the model config)
     noai        = False  # Runs the script without starting up the transformers pipeline
     aibusy      = False  # Stops submissions while the AI is working
@@ -184,7 +185,7 @@ def getModelSelection():
     while(vars.model == ''):
         modelsel = input("Model #> ")
         if(modelsel.isnumeric() and int(modelsel) > 0 and int(modelsel) <= len(modellist)):
-            vars.model = modellist[int(modelsel)-1][1]
+            vars.model = vars.model_orig = modellist[int(modelsel)-1][1]
         else:
             print("{0}Please enter a valid selection.{1}".format(colors.RED, colors.END))
     
@@ -365,7 +366,7 @@ parser.add_argument("--override_rename", action='store_true', help="Renaming sto
 parser.add_argument("--configname", help="Force a fixed configuration name to aid with config management.")
 
 args = parser.parse_args()
-vars.model = args.model;
+vars.model = vars.model_orig = args.model;
 
 if args.remote:
     vars.remote = True;
@@ -1386,23 +1387,23 @@ def lua_get_modeltype():
         return "readonly"
     if(vars.model in ("Colab", "OAI", "InferKit")):
         return "api"
-    if(vars.model in ("GPT2Custom", "NeoCustom")):
+    if(vars.model not in ("TPUMeshTransformerGPTJ",) and (vars.model in ("GPT2Custom", "NeoCustom") or vars.model_type in ("gpt2", "gpt_neo", "gptj"))):
         hidden_size = get_hidden_size_from_model(model)
-    if(vars.model in ("gpt2",) or (vars.model == "GPT2Custom" and hidden_size == 768)):
+    if(vars.model in ("gpt2",) or (vars.model_type == "gpt2" and hidden_size == 768)):
         return "gpt2"
-    if(vars.model in ("gpt2-medium",) or (vars.model == "GPT2Custom" and hidden_size == 1024)):
+    if(vars.model in ("gpt2-medium",) or (vars.model_type == "gpt2" and hidden_size == 1024)):
         return "gpt2-medium"
-    if(vars.model in ("gpt2-large",) or (vars.model == "GPT2Custom" and hidden_size == 1280)):
+    if(vars.model in ("gpt2-large",) or (vars.model_type == "gpt2" and hidden_size == 1280)):
         return "gpt2-large"
-    if(vars.model in ("gpt2-xl",) or (vars.model == "GPT2Custom" and hidden_size == 1600)):
+    if(vars.model in ("gpt2-xl",) or (vars.model_type == "gpt2" and hidden_size == 1600)):
         return "gpt2-xl"
-    if(vars.model == "NeoCustom" and hidden_size == 768):
+    if(vars.model_type == "gpt_neo" and hidden_size == 768):
         return "gpt-neo-125M"
-    if(vars.model in ("EleutherAI/gpt-neo-1.3B",) or (vars.model == "NeoCustom" and hidden_size == 2048)):
+    if(vars.model in ("EleutherAI/gpt-neo-1.3B",) or (vars.model_type == "gpt_neo" and hidden_size == 2048)):
         return "gpt-neo-1.3B"
-    if(vars.model in ("EleutherAI/gpt-neo-2.7B",) or (vars.model == "NeoCustom" and hidden_size == 2560)):
+    if(vars.model in ("EleutherAI/gpt-neo-2.7B",) or (vars.model_type == "gpt_neo" and hidden_size == 2560)):
         return "gpt-neo-2.7B"
-    if(vars.model in ("EleutherAI/gpt-j-6B",) or (vars.model == "NeoCustom" and hidden_size == 4096) or (vars.model == "TPUMeshTransformerGPTJ" and tpu_mtj_backend.params["d_model"] == 4096)):
+    if(vars.model in ("EleutherAI/gpt-j-6B",) or (vars.model == "TPUMeshTransformerGPTJ" and tpu_mtj_backend.params["d_model"] == 4096) or (vars.model_type in ("gpt_neo", "gptj") and hidden_size == 4096)):
         return "gpt-j-6B"
     return "unknown"
 
diff --git a/bridge.lua b/bridge.lua
index 2ca2eed0..39acc222 100644
--- a/bridge.lua
+++ b/bridge.lua
@@ -1038,7 +1038,7 @@ return function(_python, _bridged)
     ---@param t KoboldLib
     ---@return string
     function KoboldLib_getters.model(t)
-        return bridged.vars.model
+        return bridged.vars.model_orig
     end
 
     ---@param t KoboldLib