Developing Models via LLMOps
In this chapter, we’ll cover how to develop a large language models (LLM) while ensuring that LLMOps best practices are followed. This ensures that the developed LLM can be effectively reviewed and eventually deployed to production. The information in this chapter exemplifies a real-world use case for developing a performant LLM through LLMOps. We will be looking at the following topics:
- Creating features
- Storing features
- Retrieving features
- Selecting foundation models
- Fine-tuning models
- Tuning hyperparameters
- Automating model development