Update app.py

app.py

@@ -143,13 +143,18 @@
 import streamlit as st
 import transformers
 import torch
+import tokenizers  # Import tokenizers explicitly
 
 # Load the model and tokenizer
 model = transformers.AutoModelForSequenceClassification.from_pretrained("DeeeTeeee01/mytest_trainer_roberta-base")
 tokenizer = transformers.AutoTokenizer.from_pretrained("DeeeTeeee01/mytest_trainer_roberta-base")
 
+# Define the custom hash function for tokenizers.Tokenizer
+def tokenizer_hash_func(tokenizer):
+    return tokenizer.__str__()
+
 # Define the function for sentiment analysis
-@st.cache
+@st.cache(hash_funcs={tokenizers.Tokenizer: tokenizer_hash_func})  # Specify the custom hash function
 def predict_sentiment(text):
     # Load the pipeline
     pipeline = transformers.pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)