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Massive parameter matrices are utilized each during the self-consideration stage and within the feed-forward stage. These represent almost all of the 7 billion parameters with the product.In the training period, this constraint ensures that the LLM learns to predict tokens dependent solely on previous tokens, as opposed to foreseeable future kinds.