Update app.py

app.py

@@ -4,14 +4,14 @@ import torch
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
 # Load the model and tokenizer
-model = AutoModelForSequenceClassification.from_pretrained("ikoghoemmanuell/finetuned_fake_news_bert")
-tokenizer = AutoTokenizer.from_pretrained("ikoghoemmanuell/finetuned_fake_news_bert")
+model_name = AutoModelForSequenceClassification.from_pretrained("ikoghoemmanuell/finetuned_fake_news_bert")
+tokenizer_name = AutoTokenizer.from_pretrained("ikoghoemmanuell/finetuned_fake_news_bert")
 
 # Define the function for detecting fake news
 @st.cache_resource
 def detect_fake_news(text):
     # Load the pipeline.
-    model = transformers.pipeline("text-classification", model=model, tokenizer=tokenizer)
+    model = transformers.pipeline("text-classification", model=model_name, tokenizer=tokenizer_name)
 
     # Predict the sentiment.
     prediction = pipeline(text)