To efficiently refresh ideas and topics that may have been cleared by the model’s garbage cleanup process, you can follow these steps:
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Before starting a new prompt: Begin each new prompt or query with a brief recap or summary of the relevant context. This serves as a reminder to the model about the previous discussion and helps maintain continuity.
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Restate important details: When introducing a topic or providing background information within a prompt, restate important details from previous conversations. This helps jog the model’s “memory” and ensures that relevant information is considered in the current context.
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Use references: Make references to previous prompts, discussions, or specific details from earlier in the conversation. For example, you can mention, “As we discussed earlier…” or “In the previous prompt, we explored…”. This helps establish connections and reinforces the continuity of the conversation.
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Recap important conclusions: If any significant conclusions or decisions were reached in previous prompts, briefly recap them to ensure that they are taken into account moving forward. This helps maintain consistency and avoids repeating discussions unnecessarily.
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Provide concise reminders: When reintroducing a topic or concept that may have been cleared from the model’s memory, provide concise reminders or keywords that trigger the relevant information. This can help refresh the model’s understanding of the subject and enable it to generate more relevant responses.
By incorporating these techniques, you can effectively refresh ideas and topics within the conversation, ensuring that important information is not lost or overlooked due to the model’s garbage cleanup process.