update

src/submission/check_validity.py

@@ -42,7 +42,7 @@ def check_model_card(repo_id: str) -> tuple[bool, str]:
 
 def is_model_on_hub(model_name: str, revision: str, token: str = None, trust_remote_code=False, test_tokenizer=False) -> tuple[bool, Optional[str], Optional[AutoConfig]]:
     try:
-        config = AutoConfig.from_pretrained(model_name, revision=revision, trust_remote_code=trust_remote_code, token=token) #, force_download=True)
+        config = AutoConfig.from_pretrained(model_name, revision=revision, trust_remote_code=trust_remote_code, token=token)
         if test_tokenizer:
             try:
                 AutoTokenizer.from_pretrained(model_name, revision=revision, trust_remote_code=trust_remote_code, token=token)

src/submission/submit.py

@@ -61,12 +61,12 @@ def add_new_eval(
 
     # Is the model on the hub?
     if weight_type in ["Delta", "Adapter"]:
-        base_model_on_hub, error, _ = is_model_on_hub(model_name=base_model, revision=revision, token=H4_TOKEN, test_tokenizer=True)
+        base_model_on_hub, error, _ = is_model_on_hub(model_name=base_model, revision=revision, token=H4_TOKEN, test_tokenizer=False)
         if not base_model_on_hub:
             return styled_error(f'Base model "{base_model}" {error}')
 
     if not weight_type == "Adapter":
-        model_on_hub, error, _ = is_model_on_hub(model_name=model, revision=revision, test_tokenizer=True)
+        model_on_hub, error, _ = is_model_on_hub(model_name=model, revision=revision, test_tokenizer=False)
         if not model_on_hub:
             return styled_error(f'Model "{model}" {error}')