Interventions in machine learning models can involve three key methods: knowledge editing which updates the model's represented knowledge through techniques like LoRa; unlearning where the model forgets previous information by training it to avoid generating certain outcomes using gradient ascent; and model compression which includes weight pruning and quantization methods to reduce unnecessary weights and lower resolution representation of the model.

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