SVM with multiple features
After having performed 

X=np.array([[1,0,0,0,0],
           [0,1,0,0,0],
           [0,0,1,0,0],
           [1,0,0,1,0],
           [1,0,0,0,1]])

y=np.array([0,1,1,1,0])


you have to do the following:

y = y.reshape(1, -1)

model=svm.SVC()
model.fit(X,y)
test = np.array([1,0,1,0,0])
test = test.reshape(1,-1)
print(model.predict(test))


In future you have to scale your dataset. You can use either Standard Scaler (suggested) or MinMax Scaler.