Update app.py

app.py

@@ -7,7 +7,7 @@ import gradio as gr
 import pandas as pd
 import numpy as np
 
-from datasets import load_dataset
+from datasets import load_dataset, VerificationMode
 from apscheduler.schedulers.background import BackgroundScheduler
 from huggingface_hub import HfApi
 
@@ -31,8 +31,8 @@ YEAR_VERSION = "2023"
 os.makedirs("scored", exist_ok=True)
 
 # Display the results
-eval_results = load_dataset(RESULTS_DATASET, YEAR_VERSION, token=TOKEN, download_mode="force_redownload", ignore_verifications=True, trust_remote_code=True)
-contact_infos = load_dataset(CONTACT_DATASET, YEAR_VERSION, token=TOKEN, download_mode="force_redownload", ignore_verifications=True, trust_remote_code=True)
+eval_results = load_dataset(RESULTS_DATASET, YEAR_VERSION, token=TOKEN, download_mode="force_redownload", verification_mode=VerificationMode.NONE, trust_remote_code=True)
+contact_infos = load_dataset(CONTACT_DATASET, YEAR_VERSION, token=TOKEN, download_mode="force_redownload", verification_mode=VerificationMode.NONE, trust_remote_code=True)
 def get_dataframe_from_results(eval_results, split):
     local_df = eval_results[split]
     local_df = local_df.map(lambda row: {"model": model_hyperlink(row["url"], row["model"])})
@@ -176,7 +176,7 @@ def add_new_eval(
 
 
 def refresh():
-    eval_results = load_dataset(RESULTS_DATASET, YEAR_VERSION, token=TOKEN, download_mode="force_redownload", ignore_verifications=True,trust_remote_code=True)
+    eval_results = load_dataset(RESULTS_DATASET, YEAR_VERSION, token=TOKEN, download_mode="force_redownload", verification_mode=VerificationMode.NONE,trust_remote_code=True)
     eval_dataframe_val = get_dataframe_from_results(eval_results=eval_results, split="validation")
     eval_dataframe_test = get_dataframe_from_results(eval_results=eval_results, split="test")
     return eval_dataframe_val, eval_dataframe_test