Update app.py

app.py

@@ -50,7 +50,7 @@ def classify_paper(title, abstract):
     input_tensor = torch.tensor(item['input_ids'])[None]
     logits = classifier.model(input_tensor).logits[0]
     preds = torch.sigmoid(logits).detach().cpu().numpy()
-    result = {classifier.model.config.id2label[num]: float(prob) for num, prob in enumerate(preds) if prob > 0.1}
+    result = {classifier.model.config.id2label[num]: float(prob) for num, prob in enumerate(preds) if prob > 0.25}
     return result
     
 
@@ -81,7 +81,7 @@ with gr.Blocks(title='Paper classifier') as demo:
     
     gr.Markdown('## Examples')
     gr.Examples(
-        examples=[['https://arxiv.org/abs/1706.03762'], ['https://arxiv.org/abs/1503.04376'], ['https://arxiv.org/abs/2201.06601']],
+        examples=[['https://arxiv.org/abs/1706.03762'], ['https://arxiv.org/abs/2304.06718'], ['https://arxiv.org/abs/1307.0058']],
         inputs=arxiv_link,
         outputs=[title, abstract],
         fn=get_arxiv_title_and_abstract,