Update app.py

app.py

@@ -77,14 +77,15 @@ labels = {
     "66": "winecellar"
   }
 
+model.eval()
+
 def classify(image):
-  model.eval()
   with torch.no_grad():
     inputs = extractor(images=image, return_tensors='pt')
     outputs = model(**inputs).logits
     outputs = rearrange(outputs, '1 j->j')
+    outputs = torch.nn.functional.softmax(outputs)
     outputs = outputs.cpu().numpy()
-    outputs = (numpy.exp(outputs)) / (numpy.sum(numpy.exp(outputs)))
     return {labels[str(i)]: float(outputs[i]) for i in range(len(labels))}
 
 gradio.Interface(fn=classify,