Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
I Recently Attended The Llms In Production Conference Organized By The Mlops Community In San Francisco And Was Blown Away By The Wealth Of Knowledge And Insights Shared By The Speakers At The Conference. To Share These Learnings And Insights From Practi

I recently attended the LLMs in production conference organized by the MLOps community in San Francisco and was blown away by the wealth of knowledge and insights shared by the speakers at the conference.

To share these learnings and insights from practitioners belonging to companies like Stripe, Meta, Canva, Databricks, Anthropic, Cohere, Redis, LangChain, Chroma, Human loop and many more I have summarized the talks from the conference into a comprehensive eBook.

Sharing free copies of this eBook (compiled in partnership with the MLOps community)!

Here are the topics covered in the eBook:

✅ Challenges encountered while shipping LLMs,
✅ Approaches to deploying LLMs
✅ Building and curating datasets for reinforcement learning,
✅ LLMs for recommendation systems,
✅ Understanding the economics of LLMs and more

I'm attaching a preview to the e-book, you can fill the form below to receive the complete e-book.

Posted 9 months ago
Votes Newest


Is this a commercial ad? this seems like out of scope for this channel
Can you expand?

Posted 9 months ago
1 Answer
9 months ago
9 months ago