fix FE check inconsistency issue

src/about.py

@@ -85,6 +85,12 @@ I don’t understand where I could start to build a QA system for submission.
 
 I want to use API-based QA systems for submission, like GPT4. What should I do?
 - We don't support API-based models now but you could train your model with the GPT cache we provided: https://github.com/Pinafore/nlp-hw/tree/master/models.
+
+I want to test my model locally before submission. How could I do that?
+- In addition to tutorial test, please also ensure your model could be loaded with the below code, so it could pass the frontend check.
+```
+AutoConfig.from_pretrained(model_name, revision="main", trust_remote_code=True/False, token=ACCESS_TOKEN)
+```
 """
 
 EVALUATION_QUEUE_TEXT = """

src/submission/check_validity.py

@@ -31,7 +31,7 @@ def check_model_card(repo_id: str) -> tuple[bool, str]:
 
     return True, ""
 
-def is_model_on_hub(model_name: str, revision: str, token: str = None, trust_remote_code=False, test_tokenizer=False) -> tuple[bool, str]:
+def is_model_on_hub(model_name: str, revision: str, token: str = None, trust_remote_code=True, test_tokenizer=False) -> tuple[bool, str]:
     """Checks if the model model_name is on the hub, and whether it (and its tokenizer) can be loaded with AutoClasses."""
     try:
         config = AutoConfig.from_pretrained(model_name, revision=revision, trust_remote_code=trust_remote_code, token=token)