The best way to Construct an LLM Question Engine in 10 Minutes | LlamaIndex x Ray Crossover

Be a part of Jerry, co-founder and CEO of LlamaIndex, and Amog, Ray developer at Anyscale as they talk about key challenges with constructing and scaling LLM purposes.

Then, comply with alongside as Amog takes you thru a code tutorial which you could attempt to learn extra about of their jointly-written weblog!

Be taught Extra—Weblog Submit: https://anyscale.com/blog/build-and-scale-a-powerful-query-engine-with-llamaindex-and-rayCode: https://github.com/amogkam/llama_index_rayRay Docs: https://docs.ray.io/en/latest/Ray Overview: https://www.ray.io/

LlamaIndex: https://www.llamaindex.ai/LlamaIndex GitHub: https://github.com/jerryjliu/llama_index 

Be a part of the Group!—Twitter: https://twitter.com/raydistributedSlack: https://docs.google.com/forms/d/e/1FAIpQLSfAcoiLCHOguOm8e7Jnn-JJdZaCxPGjgVCvFijHB5PLaQLeig/viewformTalk about Discussion board: https://discuss.ray.io/

Managed Ray—For those who’re taken with a managed Ray service, try: https://www.anyscale.com/signup

#llm #machinelearning #ray #deeplearning #distributedsystems #python

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