This chapter covers
- The fine-tuning process for an LLM
- Preparing a data set to use for fine-tuning
- Using fine-tuning tools to better understand the process
Although the effects of large language models (LLMs) in various industries have been covered extensively in the mainstream media, the ubiquity and popularity of LLMs have contributed to a quiet revolution in the AI open source community. Through the spirit of open collaboration and the support of big technology companies, the ability to fine-tune AI models has become increasingly more accessible to AI enthusiasts. This opportunity has resulted in a vibrant community that is experimenting and sharing a wide range of processes and tools that can be used to better understand how fine-tuning works and how we can tune models ourselves or in teams.