Update app.py

app.py

@@ -149,16 +149,15 @@ import tokenizers  # Import tokenizers explicitly
 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
+# Define the custom hash function for tokenizers.Tokenizer (Unused in this version)
 def tokenizer_hash_func(tokenizer):
     return tokenizer.__str__()
 
-# Define the custom hash function for tokenizers.AddedToken
+# Define the custom hash function for tokenizers.AddedToken (Unused in this version)
 def added_token_hash_func(token):
     return token.__str__()
 
-# Define the function for sentiment analysis
-@st.cache_data(hash_funcs={tokenizers.Tokenizer: tokenizer_hash_func, tokenizers.AddedToken: added_token_hash_func})
+# Define the function for sentiment analysis without caching
 def predict_sentiment(text):
     # Load the pipeline
     pipeline = transformers.pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
@@ -215,4 +214,4 @@ h1 {
 </style>
 """,
 unsafe_allow_html=True
-)
+)