Update app.py

app.py

@@ -9,14 +9,14 @@ extractor = AutoFeatureExtractor.from_pretrained("andresgtn/vit-base-bean-health
 model = AutoModelForImageClassification.from_pretrained("andresgtn/vit-base-bean-health-classifier")
 
 # add to cuda?
-model.eval()
-model.to(device)
+#model.eval()
+#model.to(device)
 
 labels = dataset['train'].features['labels'].names
 
 def classify(im):
   features = extractor(im, return_tensors='pt')
-  features.to(device) # move to gpu as model, if available
+  #features.to(device) # move to gpu as model, if available
   with torch.no_grad():
     logits = model(**features).logits
   probability = torch.nn.functional.softmax(logits, dim=-1)