Building an LLMOps Stack for Large Language Models

Explore the construction and optimization of LLMOps architecture in this informative talk by Rafael and Puneet from Databricks. Delve into key components of the LLMOps stack, including MLFlow for Large Language Models (LLMs), Vector Databases, embeddings, and compute optimizations. Gain insights into the role of MLFlow in managing and streamlining LLMs, and understand the importance of Vector Databases for efficient storage, indexing, and retrieval of high-dimensional vector data. Learn about RAG strategies and techniques, as well as methods for prompt tracking and evaluation of LLMs. Discover key metrics and approaches for assessing the effectiveness of large language models. This talk, presented by LLMOps Space, a global community for LLM practitioners, offers valuable knowledge for those interested in deploying LLMs into production.

Building an LLMOps Stack for Large Language Models | LLMs