diff --git a/modeling/inference_models/generic_hf_torch/class.py b/modeling/inference_models/generic_hf_torch/class.py
index a0b7b4cb..b56a7c45 100644
--- a/modeling/inference_models/generic_hf_torch/class.py
+++ b/modeling/inference_models/generic_hf_torch/class.py
@@ -9,6 +9,8 @@ from typing import Union
 from transformers import GPTNeoForCausalLM, GPT2LMHeadModel
 from hf_bleeding_edge import AutoModelForCausalLM
 
+from transformers.utils import WEIGHTS_NAME, WEIGHTS_INDEX_NAME, TF2_WEIGHTS_NAME, TF2_WEIGHTS_INDEX_NAME, TF_WEIGHTS_NAME, FLAX_WEIGHTS_NAME, FLAX_WEIGHTS_INDEX_NAME, SAFE_WEIGHTS_NAME, SAFE_WEIGHTS_INDEX_NAME
+
 import utils
 import modeling.lazy_loader as lazy_loader
 import koboldai_settings
@@ -27,6 +29,19 @@ model_backend_name = "Huggingface"
 
 class model_backend(HFTorchInferenceModel):
 
+    def is_valid(self, model_name, model_path, menu_path):
+        base_is_valid = super().is_valid(model_name, model_path, menu_path)
+        path = False
+        gen_path = "models/{}".format(model_name.replace('/', '_'))
+        if model_path is not None and os.path.exists(model_path):
+            path = model_path
+        elif os.path.exists(gen_path):
+            path = gen_path
+
+        fnames = [WEIGHTS_NAME, WEIGHTS_INDEX_NAME, TF2_WEIGHTS_NAME, TF2_WEIGHTS_INDEX_NAME, TF_WEIGHTS_NAME, FLAX_WEIGHTS_NAME, FLAX_WEIGHTS_INDEX_NAME, SAFE_WEIGHTS_NAME, SAFE_WEIGHTS_INDEX_NAME]
+
+        return base_is_valid and any(os.path.exists(os.path.join(path, fname)) for fname in fnames)
+
     def _initialize_model(self):
         return