Update app.py

app.py

@@ -23,7 +23,7 @@ model, tokenizer = load_model_and_tokenizer()
 
 
 def get_predict(title: str, abstract: str) -> (str, float, dict):
-    tokenized_text = tokenizer(title + tokenizer.sep_token + abstact[:128], padding="max_length", truncation=True)
+    tokenized_text = tokenizer(title + tokenizer.sep_token + abstract[:128], padding="max_length", truncation=True)
 
     with torch.no_grad():
         outputs = model(tokenized_text)