Update app.py

app.py

@@ -10,11 +10,8 @@ DEVICE = torch.device("cpu")
 
 encoder = load_encoder("encoder_resnet18_simclr.pth")
 
-data = np.load("linear_probe_cifar10.npz")
-clf = LogisticRegression()
-clf.coef_ = data["coef"]
-clf.intercept_ = data["intercept"]
-clf.classes_ = np.arange(10)
+data = np.load("linear_probe_cifar10.npz", allow_pickle=True)
+clf = data["clf"].item()
 
 CLASSES = [
     "airplane","automobile","bird","cat","deer",