Practical RAG - Choosing the Right Embedding Model, Chunking Strategy, and More

Поделиться
HTML-код
  • Опубликовано: 23 ноя 2024

Комментарии • 8

  • @wernerkallmann9105
    @wernerkallmann9105 9 месяцев назад +2

    Thank you for sharing these best practice insights.

  • @rss1322
    @rss1322 23 дня назад

    Absolute gold!

  • @haunable
    @haunable 4 месяца назад +1

    Wow excellent, concise and fairly advanced. Thanks!

  • @jayhu6075
    @jayhu6075 9 месяцев назад +2

    A good explanation to prepare for building a rag model, could you make a following deep dive tutorial to thoroughly understand the process and intricacies involved? Many thx.

  • @sofluzik
    @sofluzik 8 месяцев назад +1

    Superb concise view thanks Frank

  • @darkreaper4990
    @darkreaper4990 6 месяцев назад +2

    man if you had a youtube channel where you made short videos like this teaching stuff. I would religiously follow you lol. this was more informative than all the video I have seen so far in the sense that it answered some of the most annoying questions I had (annoying as in couldn't find answer to them) and more.

  • @aninditasinhabanerjee1610
    @aninditasinhabanerjee1610 5 месяцев назад +1

    Very nice talk

  • @awakenwithoutcoffee
    @awakenwithoutcoffee 5 месяцев назад

    great talk, appreciated!: Question: when it comes to choosing the vectorstore (around @11:00): are we talking about size per "client database" or for your "complete (multiple, combined) database" ? What if our clients on average have a KB of 10 GB ?