No, it’s common to normalize the inputs for a lot of machine learning models, as this might accelerate and stabilize the training.
Some methods e.g. RandomForest classifiers are not sensitive to the input range, while e.g. neural networks are.
You would have to check the dataset creation (or just get a single sample) and check the range of the inputs the model was trained on.