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LLM Fine-Tuning

Topic: LLM

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Fine-Tuning Large Language Models

Adapt pre-trained LLMs.

Full Fine-Tuning

Update all parameters. Needs GPU memory. LoRA: Low-Rank Adaptation.

Parameter Efficient

LoRA: add adapters. Prefix tuning: add prompt tokens. Adapter fusion.

Prompt Engineering

Few-shot examples. Chain-of-thought. ReAct: reasoning + acting.

Key Takeaways

  1. Full fine-tuning updates all params
  2. LoRA efficient adapter approach
  3. Prompt engineering before fine-tuning

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