Update app.py

app.py

@@ -20,8 +20,8 @@ csv.field_size_limit(sys.maxsize)
 
 device = "cuda:0" if torch.cuda.is_available() else "cpu"
 
-tokenizer = XLNetTokenizer.from_pretrained("xlnet-base-cased")  
-model = XLNetForSequenceClassification.from_pretrained("vikvenk/ADR_Detection").to(device)
+tokenizer = AutoTokenizer.from_pretrained("vikvenk/ADR_Detection")
+model = AutoModelForSequenceClassification.from_pretrained("vikvenk/ADR_Detection")
 # build a pipeline object to do predictions
 pred = transformers.pipeline("text-classification", model=model, 
                              tokenizer=tokenizer, return_all_scores=True)