update app

app.py

@@ -3,7 +3,7 @@ import yfinance as yf
 import pandas as pd
 import numpy as np
 import torch
-from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, T5Tokenizer
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 from datetime import datetime, timedelta
 import plotly.graph_objects as go
 import plotly.express as px
@@ -37,12 +37,11 @@ def load_model():
         device_map="auto",
         trust_remote_code=True
     )
-    # FIX 2: Explicitly use T5Tokenizer (slow version for T5 architecture)
-    # and set trust_remote_code=True and use_fast=False to bypass problematic AutoTokenizer conversion
-    tokenizer = T5Tokenizer.from_pretrained(
+    # FIX 2: Use AutoTokenizer and rely SOLELY on trust_remote_code=True
+    # This forces the loading of the custom ChronosTokenizer class, bypassing the conflicting T5 conversion logic.
+    tokenizer = AutoTokenizer.from_pretrained(
         "amazon/chronos-bolt-base", 
-        trust_remote_code=True,
-        use_fast=False
+        trust_remote_code=True
     )
     return model, tokenizer