Go from large language model to market faster with Ray, Hugging Face, and LangChain

503
12.9
Опубликовано 1 июля 2024, 15:39
In this session, you’ll learn how to deploy a fully-functional Retrieval-Augmented Generation (RAG) application to Google Cloud using open-source tools and models from Ray, HuggingFace, and LangChain. You’ll learn how to augment it with your own data using Ray on Google Kubernetes Engine (GKE) and Cloud SQL’s pgvector extension, deploy any model from HuggingFace to GKE, and rapidly develop your LangChain application on Cloud Run. After the session, you’ll be able to deploy your own RAG application and customize it to your needs.

Speakers: Alex Zakonov, Brandon Royal, Stephen Allen

Watch more:
All sessions from Google Cloud Next → goo.gle/next24

#GoogleCloudNext

Event: Google Cloud Next 2024
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