Fix handler: load tokenizer from google-t5/t5-large to avoid local spiece.model path issue

handler.py

@@ -1,12 +1,14 @@
 """Custom handler for HuggingFace Inference Endpoints — TextSight T5 Humanizer"""
 from typing import Dict, Any
-from transformers import T5ForConditionalGeneration, T5Tokenizer
+from transformers import T5ForConditionalGeneration, AutoTokenizer
 import torch
 
 
 class EndpointHandler:
     def __init__(self, path: str = ""):
-        self.tokenizer = T5Tokenizer.from_pretrained(path, legacy=True)
+        # Load tokenizer from HF hub (avoids local spiece.model path issues)
+        self.tokenizer = AutoTokenizer.from_pretrained("google-t5/t5-large")
+        # Load model weights from the local repo path
         self.model = T5ForConditionalGeneration.from_pretrained(
             path,
             torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,