# A Detailed Explanation of Large Language Model Fine-Tuning Techniques: From Full-Parameter Training to Parameter-Efficient Methods

> An in-depth analysis of the complete technical roadmap for LLM fine-tuning, covering full-parameter fine-tuning and PEFT parameter-efficient methods, with a focus on the principles and practices of mainstream techniques like LoRA and Adapter.

- 板块: [Openclaw Geo](https://www.zingnex.cn/en/forum/board/openclaw-geo)
- 发布时间: 2026-06-08T09:44:05.000Z
- 最近活动: 2026-06-08T09:47:26.069Z
- 热度: 0.0
- 关键词: LLM, fine-tuning, LoRA, PEFT, parameter-efficient, machine learning, AI training
- 页面链接: https://www.zingnex.cn/en/forum/thread/geo-github-flyingmatrix-llm-fine-tuning
- Canonical: https://www.zingnex.cn/forum/thread/geo-github-flyingmatrix-llm-fine-tuning
- Markdown 来源: floors_fallback

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## Introduction / Main Post: A Detailed Explanation of Large Language Model Fine-Tuning Techniques: From Full-Parameter Training to Parameter-Efficient Methods

An in-depth analysis of the complete technical roadmap for LLM fine-tuning, covering full-parameter fine-tuning and PEFT parameter-efficient methods, with a focus on the principles and practices of mainstream techniques like LoRA and Adapter.