Embedding Prompting Knowledge into LLM Parameters via Fine-Tuning
By extending the fine-tuning process, Large Language Models can internalize knowledge about the structure and nature of a task's prompts. This information becomes embedded within the model's parameters, which consequently allows the model to perform the task effectively with less detailed or complex prompting.
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Ch.3 Prompting - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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