Yes feature extractors also have a from_pretrained method, to just load the same configuration as the one of a particular checkpoint on the hub.
e.g. if you do ViTFeatureExtractor.from_pretrained("google/vit-base-patch16-224"), it will make sure the size attribute of the feature extractor is set to 224. You could of course also just initialize it as feature_extractor = ViTFeatureExtractor(), as in this case, the feature extractor’s size attribute will be 224 by default as seen in the docs 2.
AutoFeatureExtractor is a class that aims to make it easier for people not having to specify a model-specific feature extractor. The Auto API will load the appropriate feature extractor by just specifying a model name from the hub. It’s a feature extractor, not a model. It will take care of the preprocessing.