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"
 
 # Load models and tokenizer
-tokenizer = AutoTokenizer.from_pretrained("paragon-analytics/ADRv1", token=HF_TOKEN)
-model = AutoModelForSequenceClassification.from_pretrained("paragon-analytics/ADRv1", token=HF_TOKEN).to(device)
+tokenizer = AutoTokenizer.from_pretrained("willwim/WillTest", token=HF_TOKEN)
+model = AutoModelForSequenceClassification.from_pretrained("willwim/WillTest", token=HF_TOKEN).to(device)
 
 # Build a pipeline object for predictions
 pred = transformers.pipeline("text-classification", model=model, tokenizer=tokenizer, top_k=None, device=device)