diff --git a/tpu_mtj_backend.py b/tpu_mtj_backend.py
index 8a9fa832..3f524d12 100644
--- a/tpu_mtj_backend.py
+++ b/tpu_mtj_backend.py
@@ -1303,7 +1303,7 @@ def load_model(path: str, model_type: str, badwordsids=koboldai_settings.badword
                     except Exception as e:
                         tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=koboldai_vars.revision, cache_dir="cache")
             try:
-                model     = AutoModelForCausalLM.from_pretrained(koboldai_vars.custmodpth, revision=koboldai_vars.revision, cache_dir="cache")
+                model     = AutoModelForCausalLM.from_pretrained(koboldai_vars.custmodpth, revision=koboldai_vars.revision, cache_dir="cache", use_safetensors=False)
             except Exception as e:
                 model     = GPTNeoForCausalLM.from_pretrained(koboldai_vars.custmodpth, revision=koboldai_vars.revision, cache_dir="cache")
         elif(os.path.isdir("models/{}".format(koboldai_vars.model.replace('/', '_')))):
@@ -1318,7 +1318,7 @@ def load_model(path: str, model_type: str, badwordsids=koboldai_settings.badword
                     except Exception as e:
                         tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=koboldai_vars.revision, cache_dir="cache")
             try:
-                model     = AutoModelForCausalLM.from_pretrained("models/{}".format(koboldai_vars.model.replace('/', '_')), revision=koboldai_vars.revision, cache_dir="cache")
+                model     = AutoModelForCausalLM.from_pretrained("models/{}".format(koboldai_vars.model.replace('/', '_')), revision=koboldai_vars.revision, cache_dir="cache", use_safetensors=False)
             except Exception as e:
                 model     = GPTNeoForCausalLM.from_pretrained("models/{}".format(koboldai_vars.model.replace('/', '_')), revision=koboldai_vars.revision, cache_dir="cache")
         else:
@@ -1333,7 +1333,7 @@ def load_model(path: str, model_type: str, badwordsids=koboldai_settings.badword
                     except Exception as e:
                         tokenizer = GPT2Tokenizer.from_pretrained("gpt2", revision=koboldai_vars.revision, cache_dir="cache")
             try:
-                model     = AutoModelForCausalLM.from_pretrained(koboldai_vars.model, revision=koboldai_vars.revision, cache_dir="cache")
+                model     = AutoModelForCausalLM.from_pretrained(koboldai_vars.model, revision=koboldai_vars.revision, cache_dir="cache", use_safetensors=False)
             except Exception as e:
                 model     = GPTNeoForCausalLM.from_pretrained(koboldai_vars.model, revision=koboldai_vars.revision, cache_dir="cache")