Update app.py

app.py

@@ -3,17 +3,17 @@ import re
 from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
 from datasets import load_dataset
 
+MODEL_NAME = "Pisethan/sangapac-math"
+
 # Get the token from the environment variable
 TOKEN = os.getenv("HF_API_TOKEN")
 if not TOKEN:
     raise ValueError("Hugging Face API token not found. Set it as an environment variable.")
 
-MODEL_NAME = "Pisethan/sangapac-math"
-
 # Load model and tokenizer
 try:
-    tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_auth_token=TOKEN)
-    model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME, use_auth_token=TOKEN)
+    tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, token=TOKEN)
+    model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME, token=TOKEN)
     classifier = pipeline("text-classification", model=model, tokenizer=tokenizer)
 except Exception as e:
     classifier = None
@@ -21,7 +21,7 @@ except Exception as e:
 
 # Load dataset dynamically from Hugging Face or locally
 try:
-    dataset = load_dataset("Pisethan/sangapac-math-dataset", use_auth_token=TOKEN)["train"]
+    dataset = load_dataset("Pisethan/sangapac-math-dataset", token=TOKEN)["train"]
     dataset_dict = {re.sub(r'\s+', ' ', entry["input"].strip()): entry for entry in dataset}
 except Exception as e:
     dataset_dict = {}