Fine-tune your LLMs with LangSmith and Lilac

The text discusses fine-tuning language models (LLMs) for specific applications using services like OpenAI and HuggingFace. It highlights the importance of high-quality, application-specific data in achieving consistent and high-quality behavior from LLMs. LangSmith and Lilac are tools that help manage and analyze this data to improve fine-tuning workflows. The process involves capturing traces from a prototype, importing them into Lilac for labeling and filtering, fine-tuning the model on the enriched dataset, and using the fine-tuned model in an improved application.