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Which is most effective when you want to train a model to respond faithfully to diverse natural language instructions?
①Compare performance using benchmarks.
②Train on instruction-response pairs using instruction tuning.
③Perform continual pretraining by feeding a large amount of unlabeled text.
④Split representations using unsupervised clustering.
⑤Increase the number of layers and parameters of the model.