Building an LLMOps Stack for Large Language Models | LLMs

In this talk, our speakers Rafael and Puneet from ‪@Databricks‬ talked about the construction and optimization of LLMOps architecture. They discussed various components including MLFlow for Large Language Models (LLMs), Vector Databases, embeddings, and compute optimizations.
Topics that are covered:
✅ MLFlow for LLMs: Discover the role of MLFlow in managing and streamlining LLMs.
✅ Vector Databases: Learn about the importance of Vector Databases in the LLMOps stack. Get insights into how they can aid in efficient storage, indexing, and retrieval of high-dimensional vector data.
✅ RAG strategies and techniques
✅ Prompt Tracking & Evaluation: Learn how to evaluate LLMs and the key metrics and methods for evaluating the effectiveness of your large language models.
About LLMOps Space -
LLMOps.Space is a global community for LLM practitioners. 💡📚
The community focuses on content, discussions, and events around topics related to deploying LLMs into production. 🚀
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[@rushikeshnaik779]

Thank you for the session. 🎉