into tokens you download the pre trained model in one line of code pick your data set for your own problem process the data set with the tokenizer to get training validation splits shuffle one batch um four more lines of code another four lines of code to instantiate your optimizer define your loss function pick a metric it's tensorflow so you got to compile it and then you call fit and that's it that's all you need to do use - all you need to do to fine-tune a state-of-the-art language model on your specific problem