klotz: llama 2*

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  1. This article explores how to boost the performance of small language models by using supervision from larger ones through knowledge distillation. The article provides a step-by-step guide on how to distill knowledge from a teacher model (LLama 2–70B) to a student model (Tiny-LLama) using unlabeled in-domain data and targeted prompting.
  2. Tune a base LLama2 LLM to output SQL code. with Parameter Efficient Fine-Tuning techniques to optimise the process.
    2023-12-17 Tags: , , , by klotz

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